Computer Science and Electronic Engineering MEng (Hons) Add to your prospectus

  • Offers study abroad opportunities Offers study abroad opportunities
  • Opportunity to study for a year in China Offers a Year in China
  • This degree is accreditedAccredited

Key information


  • Course length: 4 years
  • UCAS code: GHK6
  • Year of entry: 2018
  • Typical offer: A-level : ABB / IB : 33 / BTEC : D*DD
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Module details

Programme Year One

  • Digital and Integrated Electronics Design
  • Electrical Circuits and Systems
  • Mathematics 1 and 2 for Electrical Engineers
  • Engineering Skills
  • Electronic Circuits
  • Graduates for the Digital Society
  • Object-Oriented Programming

Year One Compulsory Modules

  • Graduates for the Digital Society (COMP107)
    Level1
    Credit level15
    SemesterFirst Semester
    Exam:Coursework weighting0:100
    AimsTo provide the students with a wide-ranging understanding of the discipline of computing, and to introduce students to concepts of professional ethics as well as social and legal aspects of computing.

    To equip the students with the communication, time and project management, and employability skills required for a computing professional.

    To allow the students to gain an understanding of the importance of appropriate and efficient database design strategies, at the conceptual and logical level, and how to communicate them effectively to stakeholders

    To provide the students with practical experience of database programming, including data manipulation and query in SQL.
    Learning Outcomes

    ​Identify and appraise professional, ethical, legal and social issues related to the work of a professional within the IT industry with particular regard to the BCS Codes of Conduct and Practice.

    ​Recognise employability and entrepreneurship skills that prepare students to undertake paid work experience during the course of their degree or independently

    Identify, describe and discuss economic, historical, organisational, research, and social aspects of computing as a discipline and computing in practice;

    Identify and apply principles of database conceptual design using ER and UML design methodologies

    ​Recognise database logical design principles, and issues related to database physical design;

    Use SQL as a data definition and manipulation language, and as a language for querying database

  • Object-oriented Programming (COMP122)
    Level1
    Credit level15
    SemesterSecond Semester
    Exam:Coursework weighting0:100
    Aims
    • To develop understanding of object-oriented software methodology, in theory and practice. 
    • To further develop sound principles in software design and software development. 
    • To understand basic concepts of software testing principles and software version control systems.  ​
    Learning Outcomes

    ​Describe object hierarchy structure and how to design such a hierarchy of related classes.

    Describe the concept of object polymorphism in theory and demonstrate this concept in practice. 

    ​Design and code iterators for collection-based data management. 

    ​Design simple unit tests using appropriate software tools. 

    ​Demonstrate concepts of event-driven programming and be able to design simple GUI to demonstrate this understanding. 

    ​Identify and describe the task and issues involved in the process of developing interactive products for people, and the techniques used to perform these tasks. 

  • Electronic Circuits (ELEC104)
    Level1
    Credit level15
    SemesterWhole Session
    Exam:Coursework weighting70:30
    Aims
  • ​To introduce students to fundamental electronic devices (diodes and transistors).
  • ​To show how diodes and transistors are used in amplifier and switching circuits.​

  • Learning OutcomesStudents will be able to show knowledge and understanding of the behaviour, important properties and applications of diodes and transistors.​​Students will have the ability to understand and apply equivalent circuit representations of diodes and transistors.​​

    Students will be able to demonstrate understanding of circuit biasing, the role of decoupling capacitors and the performance of some commonly used configurations and their practical significance.​​

  • Electrical Circuits and Systems (ELEC142)
    Level1
    Credit level15
    SemesterFirst Semester
    Exam:Coursework weighting70:30
    Aims
  • To become familiar with a range of circuit analytical techniques

  • ​To be able to apply the most appropriate technique for a given circuit

  • To understand and be able to analyse transient phenomena in circuits containing reactive elements
  • To understand the basic principles of operational amplifiers and analyse circuits containing them

  • To introduce students to AC circuits.

  • To provide a method for AC circuit analysis for fixed frequency supplies.

  • To extend the AC circuit analysis for variable frequency circuits (ie simple filters).

  • To extend the analysis from passive frequency dependent circuits to active circuits. ​

  • Learning Outcomes

    ​Understand Ohms Law and other fundamental principals

    Understand how circuits can be simplified using resistor combinations

    ​Understand the difference between real and ideal components

    ​Understand how to apply advanced circuit analysis techniques  (Nodal Analysis, Superposition, thevenin and Norton theorems) to  solve simple DC and AC circuit problems.

  • Digital & Integrated Electronics Design (ELEC143)
    Level1
    Credit level15
    SemesterSecond Semester
    Exam:Coursework weighting65:35
    Aims

    This module aims to provide students with knowledge of:

    • Number systems such as binary, hexadecimal, BCD
    • Laws of Boolean Algebra
    • Basic design methods for combinational and sequential logic circuits.
    • Operation of various silicon electronic devices
    • To provide students with the opportunity to understand the basic principles of silicon microelectronics design.
    • Introduce the subject in the frame of reference of basic design and problem solving.
    • To develop practical skills in the handling and measurement of components.
    • To increase the confidence of the student in undertaking material with a strong analytical and engineering content.
    Learning OutcomesUnderstanding of number systems such as binary, hexadecimal and BCD
    ​​Knowledge of the laws of Boolean Algebra

    ​​Knowledge of basic design methods for combinational and sequential logic circuits 

    ​Understanding of the application of the physical laws of semiconductor to practicle silicon electronic devices such as diodes and transistors

    ​Familiarity of the common design rules for development of layouts for the silicon devices and simple circuits

  • Engineering Skills (ELEC171)
    Level1
    Credit level15
    SemesterWhole Session
    Exam:Coursework weighting0:100
    AimsThis module covers the fundamental concepts and techniques necessary to use industrial/commercial windows-based software applications. It also attempts to create new knowledge and understanding of electrical engineering principles.
    On completion of the module, a student is expected to know and understand:
    • How to structure a scientific report or presentation.
    • The key aspects of using the formulae, functions and charts
    • The opportunities presented in MATLAB for solving complex mathematical problems
    • How to connect basic measuring equipment to electronic circuits
    • The operating principles of an Oscilloscope
    • The key aspects of microcontroller functionality and programming
    • The basic principles of electromagnetism
    • The functionality of software tools for circuit design and testing
    • The properties of diodes
    • The operating principle of power generators and electrical motors
    • The procedure to be followed for successfully completing an electrical engineering project
    • The main sustainability practical and legal issues to come into force in the near future
    • Error analysis, systematic and random errors

     

    Learning Outcomes

    ​have enhanced and harmonised IT skills with relation to:

    • University computer network
    • Technical report writing
    • Data analysis
    • Creation and delivery of presentations
    • Engineering spreadsheet analysis

    ​be creative in design, be able to evaluate results and synthesise knowledge  

    ​know how to complete individual work and be a valuable team member  

    recognise the basic building blocks of electrical circuits  

    know how to use basic measuring equipment and design software

    correlate theory in textbooks with its practical applications

    ​design and construct an electronic product

    ​to provide an appreciation of electrical engineers responsibilities in the context of sustainable development

    ​to solve mathematically oriented problems by wiring simple programmes in MATLAB

  • Mathematics I for Electrical Engineers (MATH191)
    Level1
    Credit level15
    SemesterFirst Semester
    Exam:Coursework weighting90:10
    Aims

    To bring students from varying backgrounds up to a common level in preparation for further modules in mathematics. To cover in detail the basic techniques of differential calculus,and provide an introduction to the theories of integral calculus, vectors, complex numbers and series.

    Learning Outcomes

      Understand the notion of limits on an intuitive level

    ​Differentiate functions using the product, quotient and chain rules

    ​Understand various applications of the theory of differentiation, including Maclaurin series and Taylor series

    ​Carry out simple calculations involving integration, vectors, complex numbers, and series

  • Mathematics II for Electrical Engineers (MATH192)
    Level1
    Credit level15
    SemesterSecond Semester
    Exam:Coursework weighting80:20
    Aims

    1. To provide a detailed introduction to techniques (change of variable,

        integration by parts and partial fractions) for and applications of

        one-dimensional integrals.

     

     2. To introduce partial derivatives of functions of two variables and their

        applications, e.g., for linear approximations.

     

     3. To comprehensively introduce matrices, determinants and several

        techniques for solving systems of linear equations; to introduce

        eigenvalues and eigenvectors for 2x2 matrices.

     

     4. To briefly revise or introduce the scalar and cross products of vectors

        and their basic applications.

     

     5. To give a comprehensive introduction to first-order ordinary differential

        equations (ODEs), including systems of two ODEs with constant coefficients,

        and second-order ODEs with constant coefficients.

     

     6. To introduce, time permitting, the Fourier expansion of periodic functions.

    Learning Outcomes

    Learning outcomes

     After completing the module students should be able to

     *  evaluate a range of one-dimensional integrals using standard techniques

     *  calculate partial derivatives and find the tangent plane to a surface

     *  invert 3x3 matrices and solve systems of linear equations

      *  solve basic (systems of) ODEs relevant to electrical engineering

Programme Year Two

  • Signals and Systems
  • Electronic Circuits and Systems
  • Instrumentation and Control
  • Digital Electronics and Microprocessor Systems
  • Software Engineering 1
  • Database Development
  • Operating  System Concepts
  • Communication Systems

Year Two Compulsory Modules

  • Operating System Concepts (COMP104)
    Level1
    Credit level15
    SemesterSecond Semester
    Exam:Coursework weighting80:20
    Aims
    1. To introduce students to the structure and functionality of modern operating systems.
    2. ​To explain how the principal components of computer-based systems perform their functions and how they interact with each other.

    Learning Outcomes

    be able to state the overall structure and functionality of a modern operating system and the interactions between computer hardware and user-processes.

    ​be able to identify the operations of the major components of an operating system, including the device manager, file manager, memory manager, and process manager.

    be able to ​identify the functions of system programs, including parsers, compilers, and virtual machines.

    be able to ​construct programs which demonstrate in a simple form the operation of examples of systems program, including simple compilers and programs that involve the managment of concurrent processes.

  • Software Engineering I (COMP201)
    Level2
    Credit level15
    SemesterFirst Semester
    Exam:Coursework weighting80:20
    Aims

    The module is intended to develop an understanding of the problems associated with the development of significant computing systems (that is, systems that are too large to be designed and developed by a single person,and are designed to be used by many users) and to appreciate the techniques and tools necessary to develop such systems efficiently, in a cost-effective manner.

     

    Learning Outcomes

    At the end of the module, the student is expected to

    • realise the problems in designing and building significant computer systems;
    • understand the need to design systems that fully meet the requirements of the intended users including functional and non functional elements

    • ​​appreciate the need to ensure that the implementation of a design is adequately tested to ensure that the completed system meets the specifications

    • ​b​e fully aware of the principles and practice of an O-O approach to the design and development of computer systems

    • ​​​​ be able to apply these principles in practice.​​ 

  • Database Development (COMP207)
    Level2
    Credit level15
    SemesterFirst Semester
    Exam:Coursework weighting80:20
    Aims
    1. To introduce students to the problems arising from concurrency in databases, information security considerations and how they are solved
    2. To introduce students to the problems arising from the integration of heterogeneous sources of information and the use of semi-structured data;
    3. To introduce students to non-relational databases and the economic factors involved in their selection
    4. To introduce students to techniques for analyzing large amounts of data, the security issues and commercial factors involved with them
    Learning Outcomes

    At the end of this module the student will be able to identify and apply the principles underpinning transaction management within DBMS and the main security issues involved in securing transaction;

    ​Demonstrate an understanding of advanced SQL topics;

    ​Illustrate the issues related to Web technologies as a semi-structured data representation formalism;

    ​Identify the principles underlying object relational models and the economic factors in their uptake and development;

    ​Interpret the main concepts and security aspects in data warehousing, and the concepts of data mining and commercial considerations involved in adopting the paradigm.

  • Communication Systems (ELEC202)
    Level2
    Credit level7.5
    SemesterSecond Semester
    Exam:Coursework weighting85:15
    Aims

    To present the concepts involved with signals and communication systems. Namely:

    • Basic communications theory
    • Analogue modulation: amplitude modulation
    • Analogue modulation: angle modulation
    • Sampling and quantisation
    • Digital (data) and analogue systems
    • Pulse modulation
    • Digital modulation
    • Multiplexing

    Learning Outcomes​Onsuccessful completion of this module the student should be able to understand basics on modern analogue and digital communication systems andmodulation techniques, their historical development and societal context in terms of contributing to quality of life.​ 

    On successful completion of this module the student should be able to use various signal analysis tools to analyse communication systems, such as spectrum analysis, frequency domain representations, sampling theory, quantisation. 

    ​ ​​On successful completion of this module the student should be able to describe the effect of noise on communication systems.

    ​On successful completion of this module the student should be able to describe, use and compare various analogue modulation/demodulation techniques. Understand relevant concepts such as amplitude modulation,suppressed carrier, large carrier, double sideband, single sideband, vestigialsideband, angle modulation frequency modulation, phase modulation, envelopdetector, coherent demodulator, modulation index, power efficiency, bandwidth,etc. 
    ​​ ​On successful completion of this module the student should be able to describe, use and compare various digital modulation/demodulation techniques.Understand relevant concepts, such as pulse code modulation, pulse widthmodulation, pulse position modulation, pulse amplitude modulation, amplitudeshift keying, phase shift keying, frequency shift keying, baseband system,passband system, etc.​ 
    ​​On successful completion of this module the student should be able to describe, use and compare various multiplexing techniques, such as frequencydivision multiplexing and time division multiplexing.​ 
  • Instrumentation & Control (ELEC207)
    Level2
    Credit level15
    SemesterWhole Session
    Exam:Coursework weighting95:5
    Aims

    Part A:

    To provide the student with the ability to select a suitable transducer and associated system for a given measurement application and to consider possible alternative solutions. To understand the principles of transducer operation and factors contributing to the measurement error.

    Part B:

    To provide the student with a thorough understanding of the principles of a closed loop control system via system modelling, performance analysis and controller design and synthesis.

    To provide a framework, within which students can evaluate, develop and implement the design methodologies of classical control, with applications to Electrical, Mechanical and Mechatronics systems.

    Learning Outcomes
    • ​An understanding of the physical basis of some common electrical transducers
    • A general appreciation of basic transducer specifications and their interpretation
    • An understanding of the system requirements for a typical measurement system
    • An appreciation of some common factors that can affect the performance of a measurement system.

    • An understanding of the behavior of linear systems, the derivation of mathematical models, and transfer function representation
    • A familiarity with the problem of stability, and the ability to apply standard tests for stability
    • An appreciation of the advantages and disadvantages of closed-loop feedback with regard to system response speed, sensitivity to parameters and disturbances, accuracy and stability
    • An appreciation of graphical techniques for representing control system characteristics
    • A familiarity with common types of system controller, and an ability to select the most appropriate controller for a given problem
    • An appreciation of how complete control schemes are implemented in hardware and software, and the problems of system integration.
  • Digital Electronics & Microprocessor Systems (ELEC211)
    Level2
    Credit level15
    SemesterSecond Semester
    Exam:Coursework weighting75:25
    AimsTo provide students with the ability to:
    • Design digital systems using the Algorithmic State Machine (ASM) methodology.
    • Understand the features of Programmable Logic Devices (PLDs) and use them in their designs.
    • Interface memory and other peripherals to microprocessor systems.
    • Provide knowledge of microprocessor systems with a good understanding of how basic microprocessors work.
    • Understand basic assembly language programmes.
    • Know the different data formats such as ASCII 2''s complement and floating point format and more advanced microprocessor concepts such as pipelines and Harvard architecture.
    Learning Outcomes

    ​Demonstrate a knowledge of digital electronics including combinational and sequential logic, algorithmic state machine (ASM) design techniques, Quine-McCluskey method and Karnuagh map-entered variables.

    ​Demonstrate an ability to design digital electronics using FPGA and a hardware description language.

    ​Demonstrate a knowledge of microprocessor concepts including architecture, assembly language, standard formats for negative and floating point numbers

    ​Demonstrate a knowledge of more advanced microprocessor concepts including von Neuman/ Harvard architectures, pipelining and memory cache.

    ​Demonstrate an ability to understand assembly language code and use assembly language  to write simple computer programmes on a basic microprocessor.

  • Signals and Systems (ELEC270)
    Level2
    Credit level15
    SemesterFirst Semester
    Exam:Coursework weighting45:55
    Aims

    To introduce the student to the fundamentals of the analysis of continuous- and discrete-time signals and systems.

    To equip the student with the mathematical tools that would allow him/her to design and/or analyse a linear time-invariant system, e.g. a filter.

    To present the concepts involved with signals and systems. Namely:

    • Signal Classification, Representation and Analysis
    • Fourier Series
    • Fourier Transform
    • Laplace Transform
    • Linear Time-invariant (LTI) Systems and Filters
    • Discrete-time Fourier Series
    • Discrete-time Fourier Transform
    • z-Transform
    Learning Outcomes​​

    ​After completion of the module, the student should have:

    An understanding of the use of Fourier Series to represent periodic continuous-time signals.

    An understanding of the use of the Fourier Transform to represent finite energy signals.

    An understanding of the Laplace Transform, its properties and its use in circuit and system analysis.

    An understanding of the use of Discrete-time Fourier Series to represent periodic discrete-time signals.

    An understanding of the use of the Discrete-time Fourier Transform.

    An understanding of the z-Transform, its properties and its use for discrete-time signals and systems.

    An understanding of the relationship between time and frequency domains.

    An understanding of Linear Time Invariant Systems, and filters, both in the continuous- and discrete-time domains.

    An appreciation of the relationship between the system function and the frequency response.


    ​​The ability to deal with real physcial signals and analyse, synthesise and otherwise manipulate them using available laboratory equipment.
  • Electronic Circuits and Systems (ELEC271)
    Level2
    Credit level15
    SemesterSecond Semester
    Exam:Coursework weighting70:30
    Aims
    • To understand how electronic circuits are designed and undertake some simple design exercises .
    • To understand how electronic devices can be represented by simple, linear equivalent circuits.
    • To show how complex circuits can be sub-divided into building blocks and these blocks in turn represented by linear equivalent circuits which can be analysed using standard circuit techniques.
    • To understand the interaction between the building blocks to allow estimation of important systems parameters such as gain, input output resistance etc.
    • To appreciate the importance of negative feedback in improving electronic systems performance and tolerance.
    Learning Outcomes

    ​Circuit operation

    Circuit design fundamentals

    ​Appreciation of historical perspective and state-of-the-art

Programme Year Three

You undertake an extended individual project. Recent projects have included ‘real-time GPS tracking of a vehicle fleet by mobile phones’, and ‘mobile multi-user dungeon (MUD) game using SMS messaging’. You can choose lecture-based modules from the two disciplines.

The modules for Electronic Engineering are chosen from:

  • Embedded Computer Systems
  • Neural Networks
  • Application Development with C++
  • MEng Project
  • Project Management

In addition three Computer Science modules are chosen from the following:

  • Software Engineering 2
  • Multi-Agent Systems
  • Formal Methods
  • Introduction to Computational Game Theory

Plus, up to two modules can be chosen from the list of subsidiary subjects.

Year Three Compulsory Modules

  • Neural Networks (ELEC320)
    Level3
    Credit level7.5
    SemesterSecond Semester
    Exam:Coursework weighting100:0
    Aims
  • ​Understand the basic structures and the learning mechanisms underlying neural networks within the field of artificial intelligence and examine how synaptic adaptation can facilitate learning and how input to output mapping can be performed by neural networks.
  • ​ Obtain an overview of linear, nonlinear, separable and non separable classification as well as supervised and unsupervised machine learning.
  • Learning OutcomesLearning  the advantages and main characteristics of neural networks in relation to traditional methodologies. Also, familiarity with different neural networks structures and their learning mechanisms.​

    ​​​​​​​Understanding of the neural network learning processes and their most popular types, as well as  appreciation of how neural networks can be applied to artificial intelligence problems.
  • Meng Project (ELEC440)
    LevelM
    Credit level30
    SemesterWhole Session
    Exam:Coursework weighting0:100
    Aims

    The project is intended to provide experience of all apsects of working as an individual engineer to complete a relatively complex engineering task:

    • To meet the mainrequirements of the professional institutions'' EA2 (Engineering Applications):application of engineering principles to the solution of practical problems within an accredited MEng degree course.
    • To give the student opportunity of applying capacities (knowledge, initiative, enthusiasm, etc.) to plan, carry out and control an open-ended project in a topic of choice
    • To provide experience of all aspects of working as an independent researcher
    • To complete a relatively complex engineering task.
    Learning Outcomes

    ​The project provides an experience of all aspects of working at a problem which has a complexity that is comparable with those encountered in industry. Upon successful competion of the project, the student will have developed a substantial knowledge and understanding of the main key aspects of various electrical engineering and electronics related problems.​

    ​Demonstrate the ability to manage the project in terms of aims and objectives, deliverables and milestones, time and resources and to research and gather appropriate information.


    ​Demonstrate an ability to define a problem and produce a specification that meets the approval of the project supervisor.


    ​Demonstrate an understanding of health and safety including risk assessment.


    ​Demonstration of ability to analyse technical problems either quantitatively or qualitatively and to design an experiment, system, component or process to perform that analysis based upon an agreed project specification.​

  • Application Development With C++ (ELEC362)
    Level3
    Credit level15
    SemesterFirst Semester
    Exam:Coursework weighting0:100
    Aims

    To provide students with the ability:

    • To Identify functional requirement for an application and produce an adequate specification.
    • To design a programme based on functional decomposition method.
    • To convert design into efficient C++ code.
    • To design and implement an application graphical user interface.
    • To use common components including controls in Windows based programme.
    • To implement event handlers and validate the programme functionality.
    • To work independently or as a team member in the management of application development.
    Learning OutcomesKnowledge and Understanding--On successful completion of the module, students should be able to demonstrate:
    • Knowledge of C++ as an advanced programming language.
    • Understanding of functional decomposition based and Object-oriented programme design.
    • Knowledge of the principles of system development.
    • Understanding of Windows based applications and their components.
  • Project Management (MNGT202)
    Level2
    Credit level7.5
    SemesterFirst Semester
    Exam:Coursework weighting60:40
    Aims

    The aim of this module is to introduce the student to some of the tools and constraints associated with managing both small and large projects, and with some simple costing approaches. A virtual project is undertaken by every student. The student is encouraged to adopt a project approach to current and future tasks, and to learn the language adopted by project-oriented employers.

    Learning Outcomes

    ​Practical project management

    ​Practical risk management

    ​Practical cost management

    ​Formal meeting administration and record taking

    ​Teamwork and communications

  • Embedded Computer Systems (ELEC370)
    Level3
    Credit level15
    SemesterWhole Session
    Exam:Coursework weighting100:0
    Aims

    To obtain an understanding of the construction and operation of embedded computer systems and their components. Furthermore to gain an understanding of how computer performance is dependent upon the design of computer architectures and sub-circuits.

    Learning Outcomes

Year Three Optional Modules

  • Multi-agent Systems (COMP310)
    Level3
    Credit level15
    SemesterSecond Semester
    Exam:Coursework weighting100:0
    Aims
    1. To introduce the student to the concept of an agent and  multi-agent systems, and the main applications for which they are appropriate;
    2. To introduce the main issues surrounding the design of intelligent agents;
    3. To introduce the main issues surrounding the design of a multi-agent society.
    4. To introduce a contemporary platform for implementing agents and multi-agent systems.
    Learning Outcomes
    1. Understand the notion of an agent, how agents are distinct from other software paradigms (eg objects) and understand the characteristics of applications that lend themselves to an agent-oriented solution;
    2. Understand the key issues associated with constructing agents capable of intelligent autonomous action, and the main approaches taken to developing such agents;
    3. Understand the key issues in designing societies of agents that can effectively cooperate in order to solve problems, including an understanding of the key types of multi-agent interactions possible in such systems
    4. Understand the main application areas of agent-based solutions, and be able to develop a meaningful agent-based system using a contemporary agent development platform.
  • Formal Methods (COMP313)
    Level3
    Credit level15
    SemesterSecond Semester
    Exam:Coursework weighting100:0
    Aims

    As more complex computational systems are used within critical applications, it is becoming essential that these systems are formally specified.  Such specifications are used to give a precise and unambiguous description of the required system.  While this is clearly important in criticial systems such as industrial process management and air/spacecraft control, it is also becoming essential when applications involving E-commerce and mobile code are developed.  In addition, as computational systems become more complex in general, formal specification can allow us to define the key characteristics of systems in a clear way and so help the development process.

    Formal specifications provide the basis for verification of properties of systems. While there are a number of ways in which this can be achieved, the model-checking approach is a practical and popular way to verify the temporal properties of finite-state systems. Indeed, such temporal verification is widely used within the design of critical parts of integrated circuits, has recently been used to verify parts of the control mechanism for one of NASA’s space probes, and is now beginning to be used to verify general Java programs.

    Learning Outcomes

    Upon completing this module, a student will:

    • understand the principles of standard formal methods, such as Z;
    • understand the basic notions of temporal logic and its use in relation to reactive systems;
    • understand the use of model checking techniques in the verification of reactive systems;
    • be aware of some of the current research issues related to formal methods.
  • Software Engineering II (COMP319)
    Level3
    Credit level15
    SemesterFirst Semester
    Exam:Coursework weighting100:0
    Aims

    The overall aim of this module is to introduce students to a range of advanced, near-research level topics in contemporary software engineering. The actual choice of topics will depend upon the interests of the lecturer and the topics current in the software engineering research literature at that time. The course will introduce issues from a problem (user-driven) perspective and a technology-driven perspective – where users have new categories of software problems that they need to be solved, and where technology producers create technologies that present new opportunities for software products. It will be expected that students will read articles in the software engineering research literature, and will discuss these articles in a seminar-style forum.

    Learning OutcomesUnderstand the key problems driving research and development in contemporary software engineering (eg the need to develop software for embedded systems).

    ​Be conversant with approaches to these problems, as well as their advantages, disadvantages, and future research  directions.

    ​Understand the key technological drivers behind contemporary software engineering research  (eg the increased use of the Internet leading to the need to engineer systems on and for the web).

    ​Be able to present, analyse, and give a reasoned critique of articles in the software engineering research literature. ble to read and understand articles in the research literature of software engineering.

    ​Be able to read and understand articles in the research literature of software engineering.

  • Introduction to Computational Game Theory (COMP323)
    Level3
    Credit level15
    SemesterFirst Semester
    Exam:Coursework weighting80:20
    Aims
  • to introduce the student to the notion of a game, its solutions concepts, and other basic notions and tools of game theory, and the main applications for which they are appropriate, including electricity trading markets;

  • ​to formalize the notion of strategic thinking and rational choice by using the tools of game theory, and to provide insights into using game theory in modeling applications;

  • ​to draw the connections between game theory, computer science, and economics, especially emphasizing the computational issues;

  • ​to introduce contemporary topics in the intersection of game theory, computer science, and economics;

  • Learning Outcomes

    ​Given a real world situation a student should be able to identify its key strategic aspects and based on these be able to connect them to appropriate game theoretic concepts;

    A student will understand the key connections and interactions between game theory, computer science and economics;

    ​A student will understand the impact of game theory on its contemporary applications, and be able to identify the key such application areas;

  • Digital Control and Optimisation (ELEC303)
    Level3
    Credit level15
    SemesterSecond Semester
    Exam:Coursework weighting100:0
    Aims
    • To introduce the students to the fundamentals of applied digital control
    • To familiarise the students with digital control design techniques through realistic control examples and applications
    • To introduce digital,P,PI,PID and full state feedback controller design
    • To introduce how to implement a digital control algorithm in software
    • To introduce the basic concept of optimisation
    • To introduce the conventional optimisation techniques
    • To introduce gradient based optimisation methods and their properties
    • To familiarise the student with the application of optimisation methods
    Learning Outcomes

    ​1: The student will be able to use Z transforms and state-space modelling to design and implement digital control algorithms.

     

    2: The student will be able to set-up optimisation problems and utilise conventional and gradient based methods to solve these problems.​

  • Signal Processing & Digital Filtering (ELEC309)
    Level3
    Credit level15
    SemesterSecond Semester
    Exam:Coursework weighting90:10
    Aims
    • To develop basic framework for signal processing and to demonstrate some applications.
    • To provide students with a good understanding of the types and behaviours of a number of different digital filters,

  • Learning Outcomes

    Appreciation of how to analyse FIR and IIR filters using z-transform.​

    Appreciation of the effects of quantisation.​

    Applications in waveform generators and digital audio.​

    The use of DFT, FFTand linear convolution.​knowledge of the concepts of linear time-invariant circuits and systems.

    Knowledge of samplingand filtering methodologies.

    Designing FIRdigital filters using the window(Fourier series) technique.​

    Designing IIRdigital filters using pole/zero placement, the bilineartransform or othertechniques. ​

    Using MATLAB in filter design.

  • Rf Engineering and Applied Electromagnetics (ELEC311)
    Level3
    Credit level7.5
    SemesterFirst Semester
    Exam:Coursework weighting100:0
    Aims

    This module aims to introduce students the fundamentalconcepts of high frequency electromagnetics; to present and develop theunderlying theory of transmission lines (TX), including lossy TX; to introducethe Smith Chart as an important tool in TX design and analysis;  to give an appreciation of the importance ofcomputational electromagnetics its role in industrial applications; to give aclear understanding of impedance matching and related techniques; to introducethe concept of the scattering parameters for 2-port networks and their applicationsand measurements; to understand radio wave propagation, attenuation andreflection; and to enable students appreciate the basic understanding of RF filter, antenna andamplifier design.​

    Learning Outcomes

     

    • The essentials of RF engineering and applied EM. The circuit and field concepts and their relevance to RF systems.

    • The underlying theory and physical concepts behind transmission lines (TX) and the factors governing performance of real TEM transmission lines, and knowledge of various transmission lines in practice.​

    • Reflection coeffiecients, VSWR,and return loss in communication systems​

    • The methods of achieving matched conditions for maximum power transfer.​

    • S- parameters and their measurement and applications.​

    • An appreciation of radio propagation and antennas.​

    • Fundamental knowledge of RF components and devices, such as filters and amplifiers, for modern communicaiton systems.
  • Antennas (ELEC312)
    Level3
    Credit level7.5
    SemesterSecond Semester
    Exam:Coursework weighting100:0
    Aims
  • To introduce fundamental antenna principles and concepts based on the underlying electromagnetic theory.

  • ​To gain a good understanding of antenna theory and design​

  • Learning Outcomes

    The ability and understand the operation and fuctions of antennas

    ​​The ability to design basics antennas

  • Photonics and Optical Information Systems (ELEC313)
    Level3
    Credit level15
    SemesterFirst Semester
    Exam:Coursework weighting100:0
    Aims
    • To introduce students to the fundamental principles of opto/electronic systems for the transfer of information.
    • To introduce the duality of light as both wave and ray.
    • To show intensity and phase related optical principles.
    • To demonstrate optical information transfer through a number of applications.
    Learning OutcomesKnowledge and understanding of electronic to optical and optical to electronic conversion and associated devices.

    ​An understanding of power transfer, modulation transfer function, system transfer function and optical data storage​

    ​An understanding of information transfer via optical intensity and phase modulation.


    ​Knowledge and understanding of the duality of light.


    ​An appreciation of how to manipulate light rays and an appreciation of intensity and phase related effects of light.​


  • Electronics for Instrumentation and Communications (ELEC317)
    Level3
    Credit level15
    SemesterFirst Semester
    Exam:Coursework weighting100:0
    Aims

    To gain knowledge of a wide range of analogue components and electronics for instrumentation and communications.

    To gain a better understanding of the theory, analysis and design of analogue electronic circuits used in instrumentation and communications systems.

    To learn and use an industrial standard simulation tool (Agilent ADS) for the design of electronic systems.
    Learning Outcomes

    ​After successful completion of the module, the student should have

    • A good understanding of a wide range of analogue components, including filters, amplifiers, oscillators, mixers, and phase locked loops.
    • An understanding of the limitations of these components and how these can be overcome by design or the appropriate choice of device.
    • An understanding of how to design these components.
    • An understanding of computer aided design of electronic systems

    After successful completion of the module, the students should be able to demonstrate ability in applying knowledge of the module topics to:

    • Analyse problems associated with electronic circuits for instrumentation and communication systems
    • Select correct components for electronic system design.
    • Design an electronic system using an industrial standard CAD tool.

  • Image Processing (ELEC319)
    Level3
    Credit level7.5
    SemesterFirst Semester
    Exam:Coursework weighting100:0
    Aims

    To introduce the basic concepts of digital image processing and pattern recognition.

    Learning Outcomes

    ​After successful completion of the module, the student should have:

    • An understanding of main principles of digital image processing, and its relation to pattern recognition in images, object detection,  tracking and machine vision.
    • An appreciation of the areas of applications for various image enhancement techniques.

    ​After successful completion of the module, the student should have:

    • An understanding of the standard methods of image manipulation, representation and information extraction.

  • Organic Electronics (ELEC324)
    Level3
    Credit level7.5
    SemesterFirst Semester
    Exam:Coursework weighting100:0
    Aims

    The main aim is to make thestudents aware of the new developments in large-area, low-cost and flexible Electronics,particularly those relating to the use of conjugated polymer and fullerenebased compounds and composites.

    Learning Outcomes

    ​Knowledge and understandingof the operation of organic Schottky diode, thin-film transistors, light-emittingdiodes and photovoltaics

    ​Knowledge to analyse novel organic device models

    Ability to analyse static and dynamic organic circuits​

    ​Ability to utilise organic models to design simple organic circuits

  • Drives (ELEC331)
    Level3
    Credit level7.5
    SemesterFirst Semester
    Exam:Coursework weighting100:0
    Aims
    • To introduce students to a range of electrical machines (AC & DC) using the concepts of rotating magnetic fields, co-energy.
    • To facilitate the prediction of machine performance by the use of equivalent circuits
    Learning Outcomes
  • Digital and Wireless Communications (ELEC377)
    Level3
    Credit level15
    SemesterFirst Semester
    Exam:Coursework weighting100:0
    Aims
    • To provide an extensive coverage of the theory and practice of digital and wireless communication systems
    • To allow students to be able to design and develop digital and wireless communication systems, with an awareness of all the main factors involved and of existing and emerging technologies.

       

    Learning Outcomes

    ​After completion of the module, the student should have a good knowledge and understanding of:
    The nature of data and how it is stored and communicated.
    The limitations imposed on communication system performance and design by various factors
    How noise arises in communications systems, and its effects of noise upon communications system behaviour and performance.
    Sources and effects of mobile radio propagations.
    Design of the optimum receiver and analysis of error probability for digital communications
    How to achieve the goals of a communication system by trading off system parameters such as signal-to-noise ratio, error probability and bandwidth expenditure
    Various multiuser communication techniques

    ​On successful completion of the module, students should be able to demonstrate a knowledge in applying the module topics to:
    Specify the requirements for a digital or wireless communication system
    Design the optimum receiver for a communication system
    Analyse the performance of a communication system
    Critical thinking ability from evaluating and responding to issues such as unachievable or impractical specifications and impossible performance claims.

  • Electromagnetic Compatibility (ELEC382)
    Level3
    Credit level7.5
    SemesterSecond Semester
    Exam:Coursework weighting100:0
    AimsThe module is aimed to provide the students with advanced knowledge and skills to deal with EMC problems.The students are expected

    1. To master the fundamental EMC principles and concepts based on the underlying electromagnetic theory.
    2. ​​To study EMC standards and regulations, and be able to apply them to real world problems.
    3. ​​To be able to use advanced theory too analyse EMC problems
    4. To be able to conduct EMC measurements and tests, and also interprete the results. 
    Learning Outcomes

    ​An indepth understanding of EMC theory, standards and practice.

    ​Ability to conduct EMC tests and analysis. 

    ​Ability to conduct EMC analysis and designs

    Knowledge and skills and solve EMC problems

  • Power Generation, Transmission & Distribution (ELEC401)
    LevelM
    Credit level15
    SemesterFirst Semester
    Exam:Coursework weighting75:25
    Aims

    • To give students a generalised view of the structure of a power system.
    • To develop the ability to analyse the steady-state and transient operation of an integrated power system in terms of the electrical and other constraints on power flow.
    • To introduce the basic principles of fault analysis and electrical safety regulations.
    • To familiarise students with some basic concepts of power electronics and to provide them with the tools to design some basic circuits.
    • To understand the principles of operation of power converters.
    • To show how power electronics and machines are complementary components of drive or generating systems, through examples of practical applications.
    Learning Outcomes

    • An advanced understanding of the nature of the load on a power system and the way in which power is supplied by generators and transmitted to consumers. 
    • A clear understanding of how synchronous generators (alternators) interact with a power system in both normal and fault conditions. 
    • Knowledge of how these generators are interconnected by the high-voltage transmission grid. 
    • Advanced knowledge of complex power flow in a network. 
    • An understanding of the matrix analysis of the network and load flow analysis. 
    • Good command of the per-unit system in the analysis of large power systems. 
    • A clear understanding of the consequences of different faults on transmission and distribution networks. 
    • Good awareness of general electrical safety issues.​

    • An advanced understanding of AC-DC uncontrolled and controlled rectifiers. 
    • An understanding of pulse width modulation to control voltage and its development into switching DC-DC supplies. 
    • An understanding of the AC(-AC) voltage control. 
    • An advanced understanding of the electronic generation of AC from DC and the ability to vary frequency. 
    • An understanding of variable speed DC and AC drives. 
    • A clear understanding of the fundamental ON-OFF nature of power electronic switches and how they are controlled to vary voltage levels and frequency. 
    • Advanced knowledge of various applications of power electronics in power systems and renewable energy.​​
  • Integrated Circuits - Concepts and Design (ELEC472)
    LevelM
    Credit level15
    SemesterWhole Session
    Exam:Coursework weighting45:55
    Aims

    To understand the reasons for the predominance and importance of silicon based microelectronics to the semiconductor industry. To understand how materials, devices and circuit issues are inter-related and exploited to make the microchips that underpin the information age. To prepare students for entering the Si semiconductor industry.

    Learning OutcomesAppreciation of MOS based integrated circuit design philosophy: power, speed, yield, packing density considerations and of design trade-offs associated with materials, device and circuit limitations.

    Knowledge of how to analyse and design simple MOS logic gates and amplifier stages.

    Appreciation of historical and future development of silicon based integrated circuit technology.

    Knowledge of silicon integrated circuit technology.

    Appreciation of some IC design issues.

    Ability to use a professional design tool (Cadence) to design, layout and test by simulation digital circuit cells.

     

  • Advanced Modern Management (MNGT352)
    Level3
    Credit level7.5
    SemesterFirst Semester
    Exam:Coursework weighting100:0
    Aims

    The Aims of this module are as follows:

    • To introduce the student to various aspects of advanced modern management.
    • To develop a knowledge and understanding of modern management tools.
    • To stimulate an appreciation of management and its importance in organisational success.
    Learning Outcomes

    ​Students who complete this module will obtain a good understanding of the following:

        The scientific theory of industrial psychology and organisational behaviour.    The key components of operations and management.    The impact of supply chain and logistics to modern business.

    ​On successful completion of the module, students should be able to demonstrate ability in applying knowledge of the above topics to:

        Analysis of organisation behaviour.    Analysing of operations systems and performance evaluation.    Analysis and modelling of supply chain.

Programme Year Four

During this year, students continue compulsory modules, choose further options and undertake an extended group project. The project would normally require both hardware and software components. The compulsory modules are Management of Design and Management of Product
Development.

The Electronics options are chosen from:

  • Information Theory and Coding
  • Advanced Algorithmic Techniques
  • Communication Networks and Security
  • Knowledge Representation

or from (if not already taken):

  • Integrated Circuits - Concepts and Design
  • Communication Networks & Security
  • Advanced Signal Processing
  • Radio Propagation for Wireless Systems
  • Digital and Wireless Communications
  • Advanced Embedded Computer Systems
  • Advanced Systems Modelling and Control
  • Energy Conversion, Renewable Energy and Smart Grids
  • High Voltage Engineering
  • Information Theory and Coding
  • Measurement, Monitoring and Sensors in Power Systems
  • Microprocessor Systems
  • Plasma Engineering
  • Power Generation, Transmission and Distribution
  • Software Engineering and Programming

And three modules are chosen from the Computer Science option list:

  • Privacy and Security
  • Safety and Dependability
  • Reasoning about Action and Change
  • Biocomputation
  • Computational Intelligence
  • Formal Methods
  • Introduction to Computational Game Theory
  • Multi-Agent Systems
  • Privacy and Security
  • Reasoning about Action and Change
  • Safety and Dependability

Year Four Compulsory Modules

  • Knowledge Representation (COMP521)
    LevelM
    Credit level15
    SemesterFirst Semester
    Exam:Coursework weighting75:24
    Aims

    This module aims:

    • To introduce Knowledge Representation as a research area.
    • To give a complete and critical understanding of the notion of representation languages and logics.
    • To study modal logics and their use;
    • To study description logic and its use;
    • To study epistemic logic and its use
    • To study methods for reasoning under uncertainty
    Learning Outcomes

    The module addresses learning outcomes 2, 3, 4, 5 and 6 for the MSc in Computer Science programme, and learning outcomes 2, 3, 4, 5 and 6 for the MEng in Computer Science programme. 

    At the end of the module, the student will be able to explain and discuss the need for formal approaches to knowledge representation in artificial intelligence, and in particular the value of logic as such an approach;

    ​be able to demonstrate knowledge of the basics of propositional logic;

    ​be able to determine the truth/satisfiability of modal formula;

    ​be able to perform modal logic model checking on simple examples;

    ​be able to perform inference tasks in description logic;

    ​be able to model problems concenring agents'' knowledge using epistemic logic;

    ​be able to indicate how updates and other epistemic actions determine changes on epistemic models;

    ​have sufficient knowledge to build "interpreted systems" from a specification, and to verify the "knowledge" properties of such systems;

    ​be familiar with the axioms of a logic for knowledge of multiple agents;

    ​be able to demonstrate knowledge of the basics of probability and decision theory, and their use in addressing problems in knowledge representation;

    ​be able to model simple problems involving uncertainty, using probability and decision theory;

    ​able to perform simple Hilbert-style deductions in modal and epistemic logic;

    ​able to use tableau based methods to do inference in description logic.

  • Advanced Algorithmic Techniques (COMP523)
    LevelM
    Credit level15
    SemesterFirst Semester
    Exam:Coursework weighting75:24
    Aims
  • To provide a sound foundation concerning the design and analysis of advanaced discrete algorithms.

  • To provide a critical rational concerning advanced complexity theory and algorithmics.​
  • To provide an in-depth, systematic and critical understanding of selected significant issues at the forefront of research explorations in the design and analysis of discrete algorithms.

  • Learning Outcomes

    Describe the following classes of algorithms and design principles associated with them: recursive algorithms, graph (search-based) algorithms, greedy algorithms, algorithms based on dynamic programming, network flow (optimisation) algorithms, approximation algorithms, randomised algorithms, distributed and parallel algorithms.

    Illustrate the above mentioned classes by examples from classical algorithmic areas, current research and applications. ​

    Identify which of the studied design principles are used in a given algorithm taking account of the similarities and differences between the principles. ​

    Apply the studied design principles to produce efficient algorithmic solutions to a given problem taking account of the strengths and weaknesses of the applicable principles.

    Outline methods of analysing correctness and asymptotic performance of the studied classes of algorithms, and apply them to analyse correctness and asymptotic performance of a given algorithm.​

  • Meng Group Project (COMP591)
    LevelM
    Credit level30
    SemesterFirst Semester
    Exam:Coursework weighting0:100
    Aims
  • To give students the opportunity to work in a group, in a guided but independent fashion, on a substantial problem that allows to show innovation and/or creativity and allows to make practical use of principles, techniques and methodologies acquired elsewhere in the programme.
  • To give experience of carrying out a large piece of group work involving the synthesis of advanced information, ideas and practices in order to provide a quality solution together with an critical evaluation of the process and the solution.

  • ​To enhance communication skills, both oral and written, in particular through collaboratively producing a report that documents the conduct of the project, the solution produced and giving a critical evalution of process and solution.

  • Learning Outcomeswork effectively and cooperatively within a team, taking on various roles within the team, on a substantial problem that allows to show innovation and/or creativity and allows to make practical use of principles, techniques and methodologies acquired elsewhere in the programme;

    ​specify formally a , showing awareness of the wider context and identification of issues that such context might cause, and produce a plan to address this problem;

    ​manage their time effectively both individually as well as a team so as to carry out a project plan;
    ​​locate and synthesise general and research information on concepts, ideas, and practices, relevant to a given project;

    ​​

    ​undertake research on their own on a substantial Computer Science problem and to devise as a team an efficient solution using an appropriate methodology;

    ​​​evaluate in a critical fashion the work the group has done, and to place it in the context of related work;​

    ​prepare and deliver formal presentations, including, where appropriate, an overview of the methodology used, the design of a solution, and the demonstration of software;

    ​collaboratively produce a report describing the conduct of the project, the solution produced and giving a critical evalution of process and solution.​​

  • Information Theory and Coding (ELEC415)
    LevelM
    Credit level7.5
    SemesterSecond Semester
    Exam:Coursework weighting100:0
    Aims

    To introduce the techniques used in source coding and error correcting codes, including the use of information as a measure.

    Learning Outcomes

    ​After successful completion of the module the student should have:
    An appreciation of information sources and of the information rates
       available on real channels.
    An appreciation of techniques for making the best use of channels for
        efficient transmission with error protection.

    After successful completion of the module the student should have:
    An understanding of the basic methods of source coding and error
        correcting codes
  • Commmunications Networks & Security (ELEC461)
    LevelM
    Credit level15
    SemesterSecond Semester
    Exam:Coursework weighting100:0
    Aims
  • ​To introduce the principles of communications networks, their components and protocols.   ​
  • ​​To provide students with the tools and techniques to analyse the performance of the main communications protocols, including: link layer, MAC layer, Network Layer (IP) including the main routing protocols, the transport control protocol (TCP), and basic packet queuing theory.
  • To provide an overview of the main topic areas in network/Cyber secuity including firewalls, intrusion detection and prevention systems, key ciphers and applied cryptogrphy, and secure sockets layer (SSL).​

  • Learning Outcomes​​​​Knowledge and Understanding:

    On successful completion of the module, students should be able to demonstrate knowledge and understanding of:

    - The structure of communications networks and how these can be described and analysed using standard reference models (OSI, TCP/IP).

    - The common protocols used over the major  wired and wireless networks, and ther Interent. 

    - The concept of quality of service (QoS) as applied to networks, and the techniques for implementing it.

    - The essential parts of an Interent router and the main routing protocols used over the Interent.

    - The basic issues concerning how to secure networks and the techniques used to address these.

    ​​​​​​

    ​Intellectual Abilities:

    On successful completion of the module, students should be able to​ demonstrate the ability to apply their knowledge of the above topics to:

    - Design and analyse communications networks

    - Analyse the behaviour, and predict the performance of the communications protocols they have learned.

    - Analyse and predict the behaviour of queues in packet switched networks.

    - Analyse and predict the performance of common Internet routing algorithms when applied to differnt network topologies. 

    - Analyse QoS for communications networks. 

    - Analyse the security requirements for specific networks and network configurations.

  • Digital System Design (ELEC473)
    LevelM
    Credit level15
    SemesterWhole Session
    Exam:Coursework weighting20:80
    Aims

    To provide students with the ability to:

    • Design and synthesise digital systems using Verilog and ASM.
    • Understand the problems of meta-stability in digital systems.
    • Design microprocessors using ASM techniques.
    • Develop and test customised NIOS II systems using Altera''s System on a Programmable Chip (SOPC) builder tool and Software Build Tools (SBT)..
    Learning Outcomes

    ​Ability to design digital systems using the ASM design method.

    ​Ability to implement digital systems using the Verilog Hardware Description Language.

    ​Understanding the internal operation of a MIPS processor.

    ​Ability to implement a SOPC system using Quartus Nios-II.

  • Management of Design (MNGT413)
    LevelM
    Credit level7.5
    SemesterSecond Semester
    Exam:Coursework weighting85:15
    Aims

    To enable students to develop a general understanding of a wide range of aspects of the design function in a manufacturing company and its management, and in particular a comprehensive understanding of the Design Process.

    The core of the module is a detailed study of a six-phase model of the Design Process derived from several authors and BS7000: Product Planning and Feasibility; Design Specification; Conceptual Design; Embodiment Design; Detail Design; Post-Design-Release.

    Learning Outcomes

Year Four Optional Modules

  • Biocomputation (COMP305)
    Level3
    Credit level15
    SemesterFirst Semester
    Exam:Coursework weighting80:20
    Aims
    1. ​​​​​​T​o introduce students to some of the established work in the field of neural computation.​​
    2. To highlight some contemporary issues within the domain of neural computation with regard to biologically-motivated computing particularly in relation to multidisciplinary research.​
    3. ​To equip students with a broad overview of the field of evolutionary computation, placing it in a historical and scientific context.​
    4. To emphasise the need to keep up-to-date in developing areas of science and technology and provide some skills necessary to achieve this.
    5. ​To enable students to make reasoned decisions about the engineering of evolutionary ("selectionist") systems.​

    Learning OutcomesAccount for biological and historical developments neural computation​

    ​Describe the nature and operation of MLP and SOM networks and when they are used​

    ​Assess the appropriate applications and limitations of ANNs

    ​​Apply their knowledge to some emerging research issues in the field​

    ​Understand how selectionist systems work in general terms and with respect to specific examples​

    ​Apply the general principles of selectionist systems to the solution of a      number of real world problems​

    ​Understand the advantages and limitations of selectionist approaches and have a considered view on how such systems could be designed​

  • Multi-agent Systems (COMP310)
    Level3
    Credit level15
    SemesterSecond Semester
    Exam:Coursework weighting100:0
    Aims
    1. To introduce the student to the concept of an agent and  multi-agent systems, and the main applications for which they are appropriate;
    2. To introduce the main issues surrounding the design of intelligent agents;
    3. To introduce the main issues surrounding the design of a multi-agent society.
    4. To introduce a contemporary platform for implementing agents and multi-agent systems.
    Learning Outcomes
    1. Understand the notion of an agent, how agents are distinct from other software paradigms (eg objects) and understand the characteristics of applications that lend themselves to an agent-oriented solution;
    2. Understand the key issues associated with constructing agents capable of intelligent autonomous action, and the main approaches taken to developing such agents;
    3. Understand the key issues in designing societies of agents that can effectively cooperate in order to solve problems, including an understanding of the key types of multi-agent interactions possible in such systems
    4. Understand the main application areas of agent-based solutions, and be able to develop a meaningful agent-based system using a contemporary agent development platform.
  • Formal Methods (COMP313)
    Level3
    Credit level15
    SemesterSecond Semester
    Exam:Coursework weighting100:0
    Aims

    As more complex computational systems are used within critical applications, it is becoming essential that these systems are formally specified.  Such specifications are used to give a precise and unambiguous description of the required system.  While this is clearly important in criticial systems such as industrial process management and air/spacecraft control, it is also becoming essential when applications involving E-commerce and mobile code are developed.  In addition, as computational systems become more complex in general, formal specification can allow us to define the key characteristics of systems in a clear way and so help the development process.

    Formal specifications provide the basis for verification of properties of systems. While there are a number of ways in which this can be achieved, the model-checking approach is a practical and popular way to verify the temporal properties of finite-state systems. Indeed, such temporal verification is widely used within the design of critical parts of integrated circuits, has recently been used to verify parts of the control mechanism for one of NASA’s space probes, and is now beginning to be used to verify general Java programs.

    Learning Outcomes

    Upon completing this module, a student will:

    • understand the principles of standard formal methods, such as Z;
    • understand the basic notions of temporal logic and its use in relation to reactive systems;
    • understand the use of model checking techniques in the verification of reactive systems;
    • be aware of some of the current research issues related to formal methods.
  • Introduction to Computational Game Theory (COMP323)
    Level3
    Credit level15
    SemesterFirst Semester
    Exam:Coursework weighting80:20
    Aims
  • to introduce the student to the notion of a game, its solutions concepts, and other basic notions and tools of game theory, and the main applications for which they are appropriate, including electricity trading markets;

  • ​to formalize the notion of strategic thinking and rational choice by using the tools of game theory, and to provide insights into using game theory in modeling applications;

  • ​to draw the connections between game theory, computer science, and economics, especially emphasizing the computational issues;

  • ​to introduce contemporary topics in the intersection of game theory, computer science, and economics;

  • Learning Outcomes

    ​Given a real world situation a student should be able to identify its key strategic aspects and based on these be able to connect them to appropriate game theoretic concepts;

    A student will understand the key connections and interactions between game theory, computer science and economics;

    ​A student will understand the impact of game theory on its contemporary applications, and be able to identify the key such application areas;

  • Privacy and Security (COMP522)
    LevelM
    Credit level15
    SemesterFirst Semester
    Exam:Coursework weighting75:24
    Aims

    The aims of this module are:

    • to introduce students to the major problems and solution approaches in the area of computer and Internet privacy, confidentiality and security.
    • to provide a theoretical framework for subsequent research in these challenging areas.

    Learning Outcomes

    At the end of the module, students should understand the main problems in security, confidentiality and privacy in conputers and in networks, and the reasons for their importance.


    At the end of the module, students should understand the main approaches adopted for their solution and/or mitigation, together with the strengths and weaknesses of each of these approaches

    ​At the end of the module, students should understand the main encryption algorithms and protocols 

    ​At the end of the module, students should appreciate the application of encryption algorithms to secure messaging, key distribution and exchange, authentication and electronic payment systems

    ​At the end of the module, students should understand the use of epistemic logics for formal modeling of security and privacy protocols.

    ​At the end of the module, students should understand the legal and ethical issues related to securit, confidentiality and privacy.

  • Safety and Dependability (COMP524)
    LevelM
    Credit level15
    SemesterSecond Semester
    Exam:Coursework weighting75:25
    Aims
    To provide a critical and in-depth understanding of all aspects of software safety and dependability; including issues realting to security, reliability and trustworthiness.

  • ​To provide a broad understanding of the state-of-the-art software engineering techniques currently used to address safety and dependability issues.

  • ​To profide an overview of the contemporary research issues relating to software safety and dependability.

  • Learning Outcomes

    At the end of the module, a student will understand some of the problems associated with the use of computer software in critical applications where safety, security and trust are issues.

    ​At the end of the module, a student willunderstand some of the contemporary mechanisms for ensuring dependability and reliability.

    ​At the end of the module, a student will understand a variety of approaches to the design and development of safe and dependable systems.

    ​At the end of the module, a student will understand formal verification techniques in relation to the assessment of safety and dependability.

    ​At the end of the module, a student will  be aware of some of the contemporary research problems in the areas of safety, security, dependability and trust.

  • Reasoning About Action and Change (COMP525)
    LevelM
    Credit level15
    SemesterSecond Semester
    Exam:Coursework weighting75:25
    Aims
    1. give the student a feel for several formalisms that deal with change
    2. show how logics can be used to specify and verify dynamic systems​

    3. give students a deeper knowledge of the semantics of such systems​

    4. develop awareness of the usual trade-off between expressivity and complexity of logical languages​  

      Learning OutcomesProvide formal specifications, using a logical language, of informal problem descriptions.

      Verify simple properties of models.​

      Produce simple logical proofs.​

      Understand how temporal logics relate to each other.​

      Understand and use model checkers.​

      ​Understand and be able to explain and fomulate properties (such as "safety", "fairness" and "liveness") of systems and be able to formulate simple instances of them.

    1. Computational Intelligence (COMP575)
      LevelM
      Credit level15
      SemesterSecond Semester
      Exam:Coursework weighting100:0
      Aims

      ​Understand the basic structures and the learning mechanisms underlying neural networks within the field of artificial intelligence and examine how synaptic adaptation can facilitate learning and how input to output mapping can be performed by neural networks.

      Obtain an overview of linear, nonlinear, separable and non separable classification as well as supervised and unsupervised mapping.

      Understand the benefit of adopting naturally inspired techniques to implement optimisation of complex systems and acquire the fundamental knowledge in various evolutionary techniques.

      Become familiar with the basic concepts of systems optimisation and its role in natural and biological systems and entities.​

      Learning Outcomes

      ​Learning  the advantages and main characteristics of neural networks in relation to traditional methodologies. Also, familiarity with different neural networks structures and their learning mechanisms.

      ​Appreciation of the advantages of evolutionary-related approaches for optimisation problems and their advantages compared to traditional methodologies. Also, understanding the different techniques of evolutionary optimisation for discrete and continuous configurations

      ​Understanding of the needs for genetic encoding and modelling for solving optimisation problems and familiarisation with the evolutionary operators and their performance.

      ​Understanding of the neural network learning processes and their most popular types, as well as  appreciation of how neural networks can be applied to artificial intelligence problems.

    2. Digital and Wireless Communications (ELEC377)
      Level3
      Credit level15
      SemesterFirst Semester
      Exam:Coursework weighting100:0
      Aims
      • To provide an extensive coverage of the theory and practice of digital and wireless communication systems
      • To allow students to be able to design and develop digital and wireless communication systems, with an awareness of all the main factors involved and of existing and emerging technologies.

         

      Learning Outcomes

      ​After completion of the module, the student should have a good knowledge and understanding of:
      The nature of data and how it is stored and communicated.
      The limitations imposed on communication system performance and design by various factors
      How noise arises in communications systems, and its effects of noise upon communications system behaviour and performance.
      Sources and effects of mobile radio propagations.
      Design of the optimum receiver and analysis of error probability for digital communications
      How to achieve the goals of a communication system by trading off system parameters such as signal-to-noise ratio, error probability and bandwidth expenditure
      Various multiuser communication techniques

      ​On successful completion of the module, students should be able to demonstrate a knowledge in applying the module topics to:
      Specify the requirements for a digital or wireless communication system
      Design the optimum receiver for a communication system
      Analyse the performance of a communication system
      Critical thinking ability from evaluating and responding to issues such as unachievable or impractical specifications and impossible performance claims.

    3. Power Generation, Transmission & Distribution (ELEC401)
      LevelM
      Credit level15
      SemesterFirst Semester
      Exam:Coursework weighting75:25
      Aims

      • To give students a generalised view of the structure of a power system.
      • To develop the ability to analyse the steady-state and transient operation of an integrated power system in terms of the electrical and other constraints on power flow.
      • To introduce the basic principles of fault analysis and electrical safety regulations.
      • To familiarise students with some basic concepts of power electronics and to provide them with the tools to design some basic circuits.
      • To understand the principles of operation of power converters.
      • To show how power electronics and machines are complementary components of drive or generating systems, through examples of practical applications.
      Learning Outcomes

      • An advanced understanding of the nature of the load on a power system and the way in which power is supplied by generators and transmitted to consumers. 
      • A clear understanding of how synchronous generators (alternators) interact with a power system in both normal and fault conditions. 
      • Knowledge of how these generators are interconnected by the high-voltage transmission grid. 
      • Advanced knowledge of complex power flow in a network. 
      • An understanding of the matrix analysis of the network and load flow analysis. 
      • Good command of the per-unit system in the analysis of large power systems. 
      • A clear understanding of the consequences of different faults on transmission and distribution networks. 
      • Good awareness of general electrical safety issues.​

      • An advanced understanding of AC-DC uncontrolled and controlled rectifiers. 
      • An understanding of pulse width modulation to control voltage and its development into switching DC-DC supplies. 
      • An understanding of the AC(-AC) voltage control. 
      • An advanced understanding of the electronic generation of AC from DC and the ability to vary frequency. 
      • An understanding of variable speed DC and AC drives. 
      • A clear understanding of the fundamental ON-OFF nature of power electronic switches and how they are controlled to vary voltage levels and frequency. 
      • Advanced knowledge of various applications of power electronics in power systems and renewable energy.​​
    4. High Voltage Engineering (ELEC407)
      LevelM
      Credit level15
      SemesterSecond Semester
      Exam:Coursework weighting80:20
      Aims
      1. The module aims to provide students with:

        (1)  knowledge of the role and importance of high voltage engineering and insulation in power delivery systems. and ​a clear understanding of the underlying theories and principles in relation to network transients, insulation degradation and operation of modern advanced  electrical apparatus.

      (2) ​opportunities to develop subject specific and transferrable skills in deriving technical solutions in response to system requirements and safety risks.

      (3) appreciation of practically important issues in executing industrial projects and the latest research development in relation to modelling and experiment of gas discharges.

      Learning Outcomes

      ​​On successful completion of the module, students are expected to:


      (1) have knowledge of the history of power generation and high voltage engineering and their current development trend, especially high voltage direct current (HVDC) transmission systems.

      ​(2) understand the objectives of insulation design and high voltages testing.

      ​(3) have in-depth knowledge in electrical discharge mechanisms and breakdown in gases, liquids, and solid materials including air, SF6, oil and polymer materials.

      ​(4) be familiar with high voltage testing systems including high voltage generation circuits, voltage waveforms, test systems, and methods of voltage and current measurement.

      ​(5) gain knowledge and understanding of the operation principles of modern electrical apparatuses including circuit breakers, insulators, transformers, surge arrestors, etc and develop skills for the design of test systems and test strategy for these apparatuses.

      (6) ​understand the technical challenges associated with insulation behaviour of polymer material under HVDC stress.

    5. Radio Propagation for Wireless Systems (ELEC411)
      LevelM
      Credit level7.5
      SemesterSecond Semester
      Exam:Coursework weighting100:0
      Aims
    6. To develop an appreciation and understanding of radio propagation mechanisms.

    7. ​To introduce and apply radio propagation models to applications​

    8. Learning Outcomes

      ​Ability to solve basic radio propgation problems

      ​​Ability to conduct radio system coverage and planning

    9. Information Theory and Coding (ELEC415)
      LevelM
      Credit level7.5
      SemesterSecond Semester
      Exam:Coursework weighting100:0
      Aims

      To introduce the techniques used in source coding and error correcting codes, including the use of information as a measure.

      Learning Outcomes

      ​After successful completion of the module the student should have:
      An appreciation of information sources and of the information rates
         available on real channels.
      An appreciation of techniques for making the best use of channels for
          efficient transmission with error protection.

      After successful completion of the module the student should have:
      An understanding of the basic methods of source coding and error
          correcting codes
    10. Measurement, Monitoring & Sensors (ELEC421)
      LevelM
      Credit level15
      SemesterWhole Session
      Exam:Coursework weighting80:20
      Aims

      This module aims to provide students with:

      • The philosophical differences between measurement and monitoring systems.
      • The role of sensors in providing inputs to these sytems.
      • The output requirements for measurement systems and monitoring systems.
      • The need to provide information without the surfeit of data.
      • The application of sensors, measurement systems and monitoring systems for electrical energy and power system networks.
      Learning OutcomesTo know and comprehend the interrelations between sensors, measurement transducer, measurement systems and monitoring systems. ​To have a firm understanding of the modulation techniques and sensor types for energy and power system networks measurement and monitoring.

      ​To understand the need for monitoring and measurement in an energy and power system network.

      To understand the potential advantages for using the informaton from such sensors etc., for managing energy and power network assets. 

    11. Microprocessor Systems (ELEC422)
      LevelM
      Credit level15
      SemesterSecond Semester
      Exam:Coursework weighting0:100
      Aims

      This module provides an understanding of the construction and operation of microprocessor based systems. Students are introduced to programming at low level and interfacing microprocessors to other components.

      Learning Outcomes

      ​On successful completion of the module students should have sufficient skill in both hardware and software to be able to use microprocessors in typical engineering applications.

      ​On successful completion of the module students should be able to programe the Cortex M series in Assembly Language.

      ​On successful completion of the module students should be able to interface additional components to the AHB-Lite bus and understand the operation of the AHB-Lite bus.

      ​On successful completion of the module students should be able to use a real-time operating system to create a multithreaded program runing on a Cortex M series device.

    12. Software Engineering and Programming (ELEC431)
      LevelM
      Credit level15
      SemesterFirst Semester
      Exam:Coursework weighting0:100
      Aims

      This module aims to equip students with knowledge of two most popular programming languages, C++ and MATLAB, an understanding of the Functional Decomposition method for program design, and practical skills of designing and coding software for engineering applications based on a problem specification.

      Learning Outcomes

      Knowledge and Understanding

      On successful completion of the module, students should be able to demonstrate their

      • appreciation of software as an "engineered product" and its development procedure;
      • understanding of established engineering principles, such as abstraction, modularity and information hiding;
      • knowledge of MATLAB and C++ as programming languages commonly used for enginnering computation and modelling, and their pros and cons for different applications requirements.
      • knowledge of logic structures, data types, user sub-routines (functions), operater precedancy, and the availability of special functions or tool boxes in MATLAB for signal analysis, image processing, filter design, and simulation of electrical systems.

      Intellectual Abilities​

      On successful completion of the module, students should be able to
      • analyse and determine the suitability of a programming language based on the nature of the problem;
      • based on relevant software engineering principles, decompose a problem specification into well defined functional blocks (modules) and design the overall program structure;
      • propose coding algorithms based on their knowledge of the programming languages to efficiently implement the software design;
      • design and carry out a test strategy to assess the soundness of the software and make subsequent improvement to design and code;
      • choose and correctly use appropriate tool boxes or functions for a given computational or data processing need in Matlab.
    13. Energy Conversion, Renewable Energy & Smart Grid (ELEC435)
      LevelM
      Credit level15
      SemesterSecond Semester
      Exam:Coursework weighting50:50
      Aims

      To develop a good understanding of different renewable energy sources and the principle of energy conversion from renewable sources into electricity.

      To develop an appreciation of the operation of a micro grid and basic principle of smart grid technologies and associated engineering.

      To gain a good understanding of the reality of the energy and power systems in industry.

      Learning Outcomes

      ​Knowledge of wind, wave, solar and hydropower energy sources, their energy density and its effects on land usage and an introduction to the theory of conversion from the original form to the electrical energy.​

      ​An appreciation of typical configuration of wind power generation systems including wind turbine, generator and power electronic converters and how the wind power generation system operated and connected with the power grid.​

      ​Knowledge of micro-grid​ embedded with renewable energy sources and the operation of an active distribution networks.​

      An appreciation of smart grid technologies and applications of smart meters and active demand management.​

      ​Reliablity and stability of power systems, inlcuding rotor-angle stability, frequency stability, and voltage stability, and how will those terms envolve under smart grid technologies. 

    14. Commmunications Networks & Security (ELEC461)
      LevelM
      Credit level15
      SemesterSecond Semester
      Exam:Coursework weighting100:0
      Aims
    15. ​To introduce the principles of communications networks, their components and protocols.   ​
    16. ​​To provide students with the tools and techniques to analyse the performance of the main communications protocols, including: link layer, MAC layer, Network Layer (IP) including the main routing protocols, the transport control protocol (TCP), and basic packet queuing theory.
    17. To provide an overview of the main topic areas in network/Cyber secuity including firewalls, intrusion detection and prevention systems, key ciphers and applied cryptogrphy, and secure sockets layer (SSL).​

    18. Learning Outcomes​​​​Knowledge and Understanding:

      On successful completion of the module, students should be able to demonstrate knowledge and understanding of:

      - The structure of communications networks and how these can be described and analysed using standard reference models (OSI, TCP/IP).

      - The common protocols used over the major  wired and wireless networks, and ther Interent. 

      - The concept of quality of service (QoS) as applied to networks, and the techniques for implementing it.

      - The essential parts of an Interent router and the main routing protocols used over the Interent.

      - The basic issues concerning how to secure networks and the techniques used to address these.

      ​​​​​​

      ​Intellectual Abilities:

      On successful completion of the module, students should be able to​ demonstrate the ability to apply their knowledge of the above topics to:

      - Design and analyse communications networks

      - Analyse the behaviour, and predict the performance of the communications protocols they have learned.

      - Analyse and predict the behaviour of queues in packet switched networks.

      - Analyse and predict the performance of common Internet routing algorithms when applied to differnt network topologies. 

      - Analyse QoS for communications networks. 

      - Analyse the security requirements for specific networks and network configurations.

    19. Advanced Embedded Systems (ELEC470)
      LevelM
      Credit level15
      SemesterWhole Session
      Exam:Coursework weighting85:15
      AimsThis module covers material for understanding and designingadvanced embedded computer systems. Key topics include computer architecture, low-powerdesign, hardware/software co-design and logic synthesis techniques.
      Learning Outcomes

      Students will achieve a full understanding of modernembedded systems including computer architecture, low-power design, hardware/softwareco-design and logic synthesis techniques.

      ​On successful completion the student should be able to understand published data concerning use of typical computer system design and components.

    20. Integrated Circuits - Concepts and Design (ELEC472)
      LevelM
      Credit level15
      SemesterWhole Session
      Exam:Coursework weighting45:55
      Aims

      To understand the reasons for the predominance and importance of silicon based microelectronics to the semiconductor industry. To understand how materials, devices and circuit issues are inter-related and exploited to make the microchips that underpin the information age. To prepare students for entering the Si semiconductor industry.

      Learning OutcomesAppreciation of MOS based integrated circuit design philosophy: power, speed, yield, packing density considerations and of design trade-offs associated with materials, device and circuit limitations.

      Knowledge of how to analyse and design simple MOS logic gates and amplifier stages.

      Appreciation of historical and future development of silicon based integrated circuit technology.

      Knowledge of silicon integrated circuit technology.

      Appreciation of some IC design issues.

      Ability to use a professional design tool (Cadence) to design, layout and test by simulation digital circuit cells.

       

    21. Advanced Signal Processing (ELEC474)
      LevelM
      Credit level15
      SemesterWhole Session
      Exam:Coursework weighting75:25
      Aims
      • To develop higher level signal processing techniques and apply them to some problems.
      • To develop different types filters and demonstrate their applications.
      Learning Outcomes

      Onsuccessful completion of this module the student should be able to explainconcepts of time and frequency domain descriptions of signals.

      Onsuccessful completion of this module the student should be able to describe,use and design ''fixed'' filter for different types of noise reduction tasks.

      ​​

      Onsuccessful completion of this module the student should be able to explainand use auto-correlation and cross-correlation.

      Onsuccessful completion of this module the student should be able to describe,use and design linear predictor and matched filter, and explain theirapplications.

      Onsuccessful completion of this module the student should be able to describe,use and design FIR Wiener filters for different tasks, and explain theirapplications.​

      Onsuccessful completion of this module the student should be able to describe,use and design FIR adaptive filters, and explain their applications.

      Onsuccessful completion of this module the student should be able to describe,use and design Kalman filters.
    22. Advanced Systems Modelling and Control (ELEC476)
      LevelM
      Credit level15
      SemesterFirst Semester
      Exam:Coursework weighting80:20
      Aims

      The module is to introduce advanced system analysis and design techniques to the students and to develop the skills of considering engineering problems from system point of view. The aims of the module are:

      To learn the skills required for system modelling and simulation. To extend the students knowledge from time-driven system to even-driven system modelling and simulation, which covers modelling and simulation of stochastic processes.

      • To understand the principle of advanced control systems.
      • Understand principles of basic adaptive and learning systems and their applicaitons.
      • Select appropriate adaptive systems and/or learning algorithms to deal with a specific engineering problem.
      • Develop software packages using MATLAB to resolve an adaptive and/or learning problem.
      • Gain their own knowledge of the subjects of adaptive and learning systems for further development.
      Learning Outcomes

      ​After successful completion of the module, the student should have:


      An understanding of how time and event driven systems can be represented by mathematical modules.

      An understanding of how computer simulation can be implemented to help system analysis and design.

      An appreciation of how computer-aided design and simulation tools operate.

      An understanding of how random number and random process can be simulated.

      An understanding of discrete time Markov process modelling and simulation.

      An appreciation of the system optimisation.

      The principle of advanced control system design.

      An appreciation of the advantages of system identification approached to problems of industrial modelling and control and adaptive controller design by contrast to the traditional methodologies.

      A familiarity with system identification and parameter estimation of dynamic systems.

      An understanding of the system identification and adaptive control techniques.

      An ability to use the MATLAB software to model a linear dynamic system and design an adaptive controller.

      An appreciation of how adaptive control theory can be applied to various industrial systems.

      A basic understanding of stochastic automata and their applications.​

    23. Plasma System Engineering (ELEC491)
      LevelM
      Credit level7.5
      SemesterFirst Semester
      Exam:Coursework weighting100:0
      Aims

      To develop an appreciation and understanding of industrial plasma discharges and associated engineering.

      Learning Outcomes

      ​Demonstrate knowledge and understanding of the basic physical processes in plasmas relevant to industry and the uses for industrial plasma technology.

      ​Apply knowledge in the analysis of plasma creation and sustainment, its basic physical properties, its interaction with substrates and its use to produce desired technological outcomes.

    The programme detail and modules listed are illustrative only and subject to change.


    Teaching and Learning

    All programmes are taught over two semesters with examinations at the end of each semester. Modules vary from those which are assessed by examination only to others which are continuous assessment only. All programmes incorporate a substantial practical component, with an increasing emphasis on project work as you progress through to the final year. You can select your final year individual project in consultation with members of staff.