MSc FT Digital Music Processing

H6T7 / MSC

Duration:: 1 Year

Description

Based on our Digital Signal Processing (DSP) programmes, but incorporating specialist modules and a specialised project, this masters will help to you to understand not only how today’s audio and music technology works, but also to become a leader in developing the next generations of these technologies.

You can choose from modules to follow one or two pathways of study: Digital Music Processing with DSP or with Multimedia. The DSP option delves further into the techniques that can be used for processing, analysis and synthesis. It will provide you with a strong background for further DSP work or research. The Multimedia option incorporates a more general understanding of how music processing is performed in broadcasting systems and in relation to other media. This option also emphasises many of the technical issues currently of concern to industry, such as watermarking, copyright protection, and Internet streaming.

Modules

Year 1

Advanced Transform Methods

Time-frequency transforms are an important tool in the analysis and processing of signals and images. These transforms include the Fourier transform, spectrogram, discrete cosine transform, wavelet transform, and Wigner-Ville distribution. This course will introduce these various transforms and explore how they are suitable for different signal and image processing applications.

Advanced Transform Methods

Summary:
Time-frequency transforms are an important tool in the analysis and processing of signals and images. These transforms include the Fourier transform, spectrogram, discrete cosine transform, wavelet transform, and Wigner-Ville distribution. This course will introduce these various transforms and explore how they are suitable for different signal and image processing applications.
Credits:
15.0
Pre-requisites:
ELE502 or ELEM020
Aims:
This course aims to introduce transform and sub-band techniques as a pre-cursor to compression and other applications. It is the first step beyond the fundamentals of Digital Signal processing.
Objectives:
Recall a range of joint time-frequency transforms. Discuss the relative merits of different transforms. Employ the common mathematical framework underlying many transform methods. Derive various properties of different transforms. Use high performance mathematical visualization software (e.g. Matlab) to implement these transforms. Apply these transforms to signal and image processing problems, such as compression or denoising.
Core Skills:
Analyse information using mathematical models
Books:
A Wavelet Tour of Signal Processing, Third Edition: The Sparse Way, by S.G. Mallat; Academic Press, ISBN: 13: 978-0-12-374370-1

Real-Time DSP

Real-Time DSP

Credits:
15.0
Pre-requisites:
Digital signal processing, signals and systems
Aims:
1. To introduce students to DSP chips and common accompanying hardware components by familiarizing them with the Texas Instruments C6711 evaluation module. 2. To allow students to work with the software environment provided by DSP chip manufacturers and to explore the additional software constructs and mechanisms provided to allow the development of real-time applications. 3. For students to develop an understanding of whether an application must be executable in real-time and, if so, what constraints this imposes on the design of the software and the use of the hardware. 4. To encourage students to fully use and help them to interpret the large body of documentation, sample code and user manuals that exists for the topics this course will encompass. 5. To introduce students, by demonstration, platform specific and DSP chip specific debugging techniques and to appreciate the problems encountered when debugging real-time applications. 6. To positively encourage independent learning and synthesis of ideas through project work.
Objectives:
1. To introduce students to DSP chips and common accompanying hardware components by familiarizing them with the Texas Instruments C6711 evaluation module. o Students should become very familiar with the technology, its properties, strengths and weaknesses. o Students should be aware of the choices available when choosing a processor, and when to select a DSP over an ASIC or a general purpose processor. 2. To allow students to work with the software environment provided by DSP chip manufacturers and to explore the additional software constructs and mechanisms provided to allow the development of real-time applications. o Students must be able to demonstrate a working knowledge of the Texas Instruments ‘Code Composer Studio’ software package. o Students must be able to utilize the real-time specific functionality of the software environment. 3. For students to develop an understanding of whether an application must be executable in real-time and, if so, what constraints this imposes on the design of the software and the use of the hardware. o Students must be able to differentiate between real-time and non-real-time applications. o Students must appreciate how the real-time requirement has shaped the development of DSP chips and will shape their applications. 4. To encourage students to fully use and help them to interpret the large body of documentation, sample code and user manuals that exists for the topics this course will encompass. o Students are expected to use the user manuals supplied with the evaluation module to complete assignments. o Students are expected to identify when to write original applications and when to draw from existing material. 5. To introduce students, by demonstration, to platform specific and DSP chip specific debugging techniques and to appreciate the problems encountered when debugging real-time applications. o Students must successfully solve problems in a laboratory environment. 6. To positively encourage independent learning and synthesis of ideas through project work. o Students will complete a project of their own specification that is expected to demonstrate an understanding of most (if not all) of the aims and learning outcomes of this course. o Students must demonstrate the ability to critically appraise their own work. o Students are expected to present results in an unambiguous fashion and to appreciate why this is particularly difficult in the fields of both real-time applications and of audio or video applications.
Books:
C6x-Based Digital Signal Processing by N. Kehtarnavaz and B. Simsek; Prentice Hall 2000; ISBN 0130883107

Fundamentals of DSP

The purpose of this module is to introduce the general topic of Digital Signal Processing and bring students up to a common level. Students are first introduced to the behaviour of simple filters as LTI systems, represented by difference equations. Frequency response of these systems leads into the study of Discrete Fourier Transform and simple Spectral Analysis. There follow sections on designing the coefficients of LTI systems so they can be programmed to perform as filters to prescribed magnitude specifications.

Fundamentals of DSP

Summary:
The purpose of this module is to introduce the general topic of Digital Signal Processing and bring students up to a common level. Students are first introduced to the behaviour of simple filters as LTI systems, represented by difference equations. Frequency response of these systems leads into the study of Discrete Fourier Transform and simple Spectral Analysis. There follow sections on designing the coefficients of LTI systems so they can be programmed to perform as filters to prescribed magnitude specifications.
Credits:
15.0
Aims:
This module will introduce the general topic of Digital Signal Processing and bring students from diverse backgrounds up to a common level for Msc studies in DSP. This is done through lectures and an intensive laboratory programme.
Objectives:
Describe the basic operations of DSP of addition, multiplication and memory/delay. Employ these simple operators in combination to perform useful tasks such as filtering and spectral analysis. Analyse simple filter structures both analytically and empirically (using Matlab). Design digital filters to meet specifications. Formulate the parameters of a spectral analysis system to obtain adequate resolution for the given task.
Core Skills:
This course is designed to bring all MSc DSP students up to a common level. All subsequent Signal processing courses in the programme are either directly or indirectly dependent on ELEM020.
Books:
Digital Signal Processing: a computer based approach by Sanjit Mitra; McGraw-Hill 2005; ISBN 0071244670

Music and Speech Processing

This course aims to introduce students to the application of Digital Signal Processing to music and speech.

Music and Speech Processing

Summary:
This course aims to introduce students to the application of Digital Signal Processing to music and speech.
Credits:
15.0
Pre-requisites:
ELE502, ELEM020, ELEM018
Aims:
The application-oriented nature of the syllabus will reinforce the theory learned in other courses through lectures and laboratories.
Objectives:
Describe the physiology and physics involved in sound production and perception. Demonstrate how various fundamental concepts in Digital Signal Processing can be combined into systems, like a Digital Power Amplifier. Demonstrate how higher level processing components are constructed from lower level ones. Discuss how compression of speech and of music, though similar, have different requirements. Propose specific compressors for specific applications. Identify latest innovations in this area involving delivery formats such as Internet and DVD. Position their acquired knowledge in a commercial context.
Core Skills:
Students will be able to evaluate and design complex signal processing systems.
Books:
Speech Communications: Human and Machine by D.O'Shaughnessy; John Wiley & Sons Inc. 1999; ISBN 0780334493

Music Analysis and Synthesis

This course introduces students to common methods for the analysis and synthesis of digital audio. It presents in-depth studies of general approaches to the low-level analysis of audio signals, and follows these with specialised methods for the semantic analysis of music signals, including the extraction of information related to the rhythm, melody, harmony and instrumentation of recorded music. This is followed by an examination of the most important methods of sound synthesis, including wavetable, sampling, additive, subtractive, modulation, and physical modelling synthesis

Music Analysis and Synthesis

Summary:
This course introduces students to common methods for the analysis and synthesis of digital audio. It presents in-depth studies of general approaches to the low-level analysis of audio signals, and follows these with specialised methods for the semantic analysis of music signals, including the extraction of information related to the rhythm, melody, harmony and instrumentation of recorded music. This is followed by an examination of the most important methods of sound synthesis, including wavetable, sampling, additive, subtractive, modulation, and physical modelling synthesis
Credits:
15.0
Pre-requisites:
ELEM020 and ELEM018
Aims:
This module is intended to provide students with advanced training in standard and state-of-the-art techniques for music analysis and synthesis. This knowledge is relevant for the music generation, processing, recording, reproduction and distribution industries, with special emphasis on music-oriented on-line services and the development of software and hardware for musicians, musicologists, sound engineers and producers. Background in digital signal processing is essential for the understanding of analysis and synthesis processes on musical signals.
Objectives:
- Understand the specific issues involving the analysis and synthesis of musical signals and the use of the presented techniques in real-world applications. - Gain a deep understanding of sound synthesis using linear and non-linear methods - Understand and gain practice in the use of sinusoidal models and the phase vocoder as analysis/synthesis tools. - Learn about high-level music analysis techniques for event detection, beat tracking and pitch estimation in monophonic and polyphonic music. - Students will also be introduced to advanced topics related to the state-of-the-art in music analysis and its applications.
Books:
Musical Signal Processing by C. Roads, S. Pope, A Piccialli and G De Poli (Editors); Swets and Zeitlinger 1997; ISBN 9026514824

Digital Audio Effects

This course introduces digital audio effects and related subjects. The main emphasis will be on the use of digital signal processing and its applications to the creation or modification of sounds and sound effects.

Digital Audio Effects

Summary:
This course introduces digital audio effects and related subjects. The main emphasis will be on the use of digital signal processing and its applications to the creation or modification of sounds and sound effects.
Credits:
15.0
Aims:
This course covers the entire field of digital audio effects, including some depth in the subfields and related subjects. It is concerned with the use of digital signal processing and its applications to the creation or modification of sounds and sound effects. It explains what can be done in the digital processing of sounds in the form of computer algorithms and sound examples resulting from these transformations. It describes signal processing concepts and software implementations, as well as advances in filters, delays, modulators, and time-frequency processing of sound. It primarily cover time-domain, non- linear, time-segment, time-frequency, source-filter, spectral, bitstream signal processing, spatial effects, time and frequency warping, and the control of audio effects. It is a core component necessary to provide engineering students with training in advanced music and audio technologies, and to give them the technical background and skills they need to create the tools used in audio production, audio engineering, and broadcasting. The lectures assume that the students have some basic knowledge of digital signal processing, and build upon that knowledge to teach students how to analyze and modify any musical audio signal. The lectures will use standard teaching materials and sample MATLAB code and audio files. The students will also gain an understanding of the creation, modification and modelling of digital audio, and understand how the complex algorithms are used in many common applications.
Objectives:
Methods to create a physical model of a sound or musical instrument. How audio signals are filtered, and which filter is appropriate for a given task. How to create common effects, such as wah-wah, flange, vibrato, tremolo, trill, echo... How time segment processing is performed. Specialised processing techniques often applied to audio, such as nonlinear and spectral processing, and when and how they are applied. Phase vocoder technology and how phase vocoders are used to create effects. How to do time scaling and pitch shifting on a signal, and how different methods are applied for speech and music, and for polyphonic and monophonic situations.. The effects of 3d sound, and how to reproduce a 3 dimensional effect using a minimum number of channels. Gain a general knowledge of how audio effects are produced, and how each of the audio effects mentioned in class fit into a general theory of audio analysis and effect creation.
Books:
Computational Auditory Scene Analysis by D.F. Rosenthal and H.G. Okuno; Lawrence Erlbaum Assoc. 1998; ISBN 0805822836

Mobile and WLAN Technologies

Introduction to Computer Vision

In recent years, research in computer vision has made significant progress.This is largely driven by the recognition that effective visual perceptionis crucial in understanding intelligent behaviour - unless we understand how we perceive, we will never understand how we reason The first part of the course will introduce the relevant concepts and techniques in machine learning. In the second part we will show how these techniques can be applied to various areas in computer vision.

Introduction to Computer Vision

Summary:
In recent years, research in computer vision has made significant progress.This is largely driven by the recognition that effective visual perceptionis crucial in understanding intelligent behaviour - unless we understand how we perceive, we will never understand how we reason The first part of the course will introduce the relevant concepts and techniques in machine learning. In the second part we will show how these techniques can be applied to various areas in computer vision.
Credits:
15.0
Pre-requisites:
Elementary calculus, linear algebra, statistics and programming in C++ or JAVA or Matlab.
Aims:

To give an updated account of both established and ongoing research in computer vision, statistical learning theories, data mining and clustering in multivariate space. Applications in human face, gesture and visual behaviour recognition will be used to illustrate the workings in some of the state-of-the-art machine vision and imaging systems.

Objectives:

The course will cover the following topics

Relevant probability and information theory
Experimental set-up of machine learning
Hidden Markov modeling
Clustering and classification
Neural Networks

Core Skills:
the ability to adapt mathematical and statistical concepts to the various research issue in computer vision.

Interactive System Design

The main areas of study are (i) interaction and design (ii) modelling of interaction (iii) the design process (iv) design principles and (v) usability evaluation. Various types of interfaces will be considered including those encountered on the web and mobile computing devices. A historical perspective is encouraged in order to provide a means of understanding current and projected developments in the discipline and profession of interactive computer system design.

The course will include seminars and group laboratory classes in which analysis, design and evaluation methods will be used in practical contexts.Students will be expected to participate fully in the seminars by presenting and discussing their own designs and evaluations.

Students will be required to construct prototype interfaces using techniques of their own choice (e.g. Java, Director).

Interactive System Design

Summary:
The main areas of study are (i) interaction and design (ii) modelling of interaction (iii) the design process (iv) design principles and (v) usability evaluation. Various types of interfaces will be considered including those encountered on the web and mobile computing devices. A historical perspective is encouraged in order to provide a means of understanding current and projected developments in the discipline and profession of interactive computer system design.

Students will be required to construct prototype interfaces using techniques of their own choice (e.g. Java, Director).

Credits:
15.0
Pre-requisites:
An undergraduate course in HCI (for example, DCS224) is an essential pre-requisite to be able to take this course successfully.
Aims:
This course is concerned with the design of interactive computer systems. The focus is on theoretical issues and models rather than on the technology of interaction. The course is intended to provide students with insight and experience in the key issues of the design process rather than providing a comprehensive coverage of the area. Students should come away from the course with the ability to identify issues and trade-offs in the design of interaction and to be able to invent and evaluate alternative solutions to design problems.
Objectives:
Students will be able to;
Understand the issues surrounding interactive computing, including a historical perspective
Analyse and evaluate existing designs
Invent and evaluate new designs
Core Skills:
The coursework involves a substantial amount of team-working so will develop your team building skills. It will also involve written communication skills and presentation skills.

Sensors and Internet of Things

New module under development for 2012/13. Information pertaining to this module will appear once approved.

Sensors and Internet of Things

Summary:
New module under development for 2012/13. Information pertaining to this module will appear once approved.
Credits:
15.0
Aims:
New module under development for 2012/13. Information pertaining to this module will appear once approved.
Objectives:
New module under development for 2012/13. Information pertaining to this module will appear once approved.
Core Skills:
New module under development for 2012/13. Information pertaining to this module will appear once approved.
Extra Costs:
New module under development for 2012/13. Information pertaining to this module will appear once approved.

Business Technology Strategy

The Business Technology Strategy module is focused on strategic management of research and development and how technology strategy drives the commercial strategy of innovative technology-based organisations. This module complements the technical areas of the degrees by focusing on the telecommunications sector. The increased exposure to and understanding of the benefits of strategic knowledge and thinking will give the graduates a better preparation for management roles within this sector.

Business Technology Strategy

Summary:
The Business Technology Strategy module is focused on strategic management of research and development and how technology strategy drives the commercial strategy of innovative technology-based organisations. This module complements the technical areas of the degrees by focusing on the telecommunications sector. The increased exposure to and understanding of the benefits of strategic knowledge and thinking will give the graduates a better preparation for management roles within this sector.
Credits:
15.0
Pre-requisites:
MTRM019 or ELE402 or ELB3402
Aims:
Understand the importance of technology strategy to businesses and how this is linked to commercial strategy Understand the theoretical knowledge and how to apply it to real-world examples. Students will have exposure to theory and practical case studies to build up their strategic skills. Case studies will be in the International business environment, with specific interest in the UK and Asia.
Objectives:
Acquire project management and strategic management skills. Assess possible solutions to a given problem. Research a topic. Work as part of a team in organising time and sharing tasks.
Core Skills:
Manage time effectively and produce written progress reports and a final report on time. Write a report that communicates a reasoned argument in a structured, clear, concise and well-presented manner. Display effective presentation skills.

Machine Learning

This course covers methods for machine learning from signals and data, including statistical pattern recognition methods, neural networks, and clustering.

Machine Learning

Summary:
This course covers methods for machine learning from signals and data, including statistical pattern recognition methods, neural networks, and clustering.
Credits:
15.0
Aims:
The aim of the course is to give students an understanding of machine learning methods, including pattern recognition, clustering and neural networks, and to allow them to apply such methods in a range of areas.
Objectives:
Recall a range of machine learning techniques and algorithms, including neural networks and statistical methods Use concepts from probability theory in machine learning Derive and analyse properties of machine learning methods Discuss the relative merits of different machine learning techniques and approaches Apply machine learning methods to the analysis of signals and data
Books:
Pattern Classification by Duda Hart and Stork; 2nd Edition; Wiley 2001; ISBN 0471056693

Communication Theory

The module introduces the basic principles of modern communication systems. The primary objective is to provide fundamental tools and methodologies used in modelling, analysing and simulating analog and digital communication systems. The following will be covered: Signal representation and spectral analysis, probability theory and random processes, detection and estimation of analog and digital systems in the presence of noise. Simulations are performed using Matlab.

Communication Theory

Summary:
The module introduces the basic principles of modern communication systems. The primary objective is to provide fundamental tools and methodologies used in modelling, analysing and simulating analog and digital communication systems. The following will be covered: Signal representation and spectral analysis, probability theory and random processes, detection and estimation of analog and digital systems in the presence of noise. Simulations are performed using Matlab.
Credits:
15.0
Aims:
The module aims at providing the underlying principles of analog and digital communications systems. These systems are the backbone of next generation wireless communications systems, satellite communications, and data transmission networks. Special emphasis is placed on the treatment of analog communications as the necessary background to understand digital communications.
Objectives:
Objectives include understanding the principles of random processes; amplitude, angle, and pulse modulation; baseband pulse transmission; passband data transmission; spread spectrum; channel fading; information theory and error control coding.
Core Skills:
Core skills include applying step-by-step design rules and understanding of system modelling, analysis, and simulation. Performing simulations using Matlab. As well as system and subsystem design. Also understanding the intricate connections between subsystems and how each aspect of the design supports the overall goal of achieving reliable communications.

XML and Structured Documents

XML has very rapidly become an extremely popular (and much-hyped)language. We will examine

The role of XML in computer science
XML and the semantic web
XSLT as a programming language

XML and Structured Documents

Summary:
XML has very rapidly become an extremely popular (and much-hyped)language. We will examine

The role of XML in computer science
XML and the semantic web
XSLT as a programming language

Credits:
15.0
Pre-requisites:
Some knowledge of programming (preferably in Java or C++)
Aims:
This course will provide the students with an understanding of, and practical experience of, the roles of structured and semi-structured information in computer science
Objectives:
Understand and use the following;

Knowledge of XML syntax and the various specificationlanguages (DTD, schema) used to constrain the syntax
Knowledge of the type system underlying XML Schema
Knowledge of the XSLT transformation language and thevarious programming techniques (structural recursion, pattern matching) needed to use it.
Knowledge of the design issues involved in XML applications

Core Skills:
Analyse the conceptual structure of real-world information and to translate it into a formal specification

The Semantic Web

The idea of putting semantic information on the Web has been around for a long time: we now have the beginnings of a practical application. This has its foundations in what is called Description Logic, which strikes a good balance between tractability and usability. This has led to a Web language called OWL, which is at the centre of modern work on the Semantic Web: there are now useful implementations, and there are workable, if modest, applications of this technology.

The Semantic Web

Summary:
The idea of putting semantic information on the Web has been around for a long time: we now have the beginnings of a practical application. This has its foundations in what is called Description Logic, which strikes a good balance between tractability and usability. This has led to a Web language called OWL, which is at the centre of modern work on the Semantic Web: there are now useful implementations, and there are workable, if modest, applications of this technology.
Credits:
15.0
Pre-requisites:
XML and Structured Information. Knowedge of logic, its syntax and semantics (up to the first order predicate calculus)
Aims:
To show the role and usefulness of semantic information in the Web To describe a suitable logical formalism for formalising semantic information To introduce the technologies of the semantic web, and discuss their strengths and weaknesses
Objectives:
i) The reasons for using semantic information on the Web ii) Introduction to description logic iii) OWL and other web ontology languages iv) implementation: Jena and other frameworks
Core Skills:
i) Translating common sense knowledge into logical formalism ii) Programming with knowledge representation
Books:
The course textbook is Grigoris Antoniou and Frank van Harmelen, A Semantic Web Primer, second edition (MIT Press 2008)

For reference, the main resource will be the W3C website http://www.w3.org/2001/sw/ (especially the section on Publications / Articles / Interviews)

Another good reference is Baader et al. The Description Logic Handbook, 2nd Edition (Cambridge 2010)

Real-Time and Critical Systems

Most computer systems do not sit on desks but are inside machine such as cars and medical devices. This module builds on undergraduate knowledge of operating systems and software engineering to introduce techniques for real-time system development in applications where the performance of the system is critical for safety.

Real-Time and Critical Systems

Summary:
Most computer systems do not sit on desks but are inside machine such as cars and medical devices. This module builds on undergraduate knowledge of operating systems and software engineering to introduce techniques for real-time system development in applications where the performance of the system is critical for safety.
Credits:
15.0
Pre-requisites:
Software engineering (DCS325 or equivalent); Operating systems (DCS200 or equivalent); Basic knowledge of Computer Architecture is also assumed. Students will be expected to write short programs in C but the modules should be accessible able to program is another language.
Aims:
The aim of this module is to introduce students to the techniques most commonly use in industrial practice for the analysis and development of real-time and critical systems and the theory behind them. It encompasses both aspects of real-time system development and of critical system analysis. Though these topics are not necessarily linked (not all real-time systems are critical), some understanding of real-time / embedded systems provides context for the study techniques used for critical systems.
Core Skills:
Students completing this module successfully will:

Be familiar with examples of real-time systems (critical and non-critical) and aware of software related accidents.
Be able to develop embedded systems on a microcomputer using a suitable tool chain through stages of the development lifecycle.
Understand the problem of scheduling real-time systems and know about scheduling algorithms
Understand the need for and function of a typical real-time operating systems
Understand software reliability and the limits of testing
Use techniques for system modelling and design suitable for real-time systems.
Apply concepts of safety, risk and hazards to the analysis of systems, using suitable techniques for both systems and software.
Be aware of regulation and standards for the use of critical systems

Books:
Safeware: System Safety and Computers, by Nancy G. Leveson, Addison Wesley, 1995) ISBN-10: 0201119722

Real-Time Systems Development, Rob Williams, Butterworth-Heinemann, 2005, ISBN-10: 0750664711

Embedded Systems: Real-Time Operating Systems for the Arm® Cortex(TM)-M3, Jonathan Valvano, 2012, ISBN-10: 1466468866

High Performance Computing

The 12 week module involves 2 hours of timetabled lectures per week. Laboratory sessions are timetabled at 2 hours per week for 6 to 7 weeks only. The course syllabus adopts a hands-on programming stance. In addition it focuses on algorithms and architectures to familiarise students with message-passing systems ((MPI) as adopted by industry.

Parallel computing, which implies the simultaneous execution of several processes for solving a single problem, is a mainstream subject with wide ranging implications for computer architecture, algorithms design and programming. The UK has been at the forefront of this technology through its involvement in the development of several innovtive architectures. Queen Mary has been involved with Parallel Computing for more than a decade. In this course, students will be introduced to parallel computing and will gain first hand experience in relevant techniques.

Laboratory work will be based on the MPI (Message Passing Interfaces) standard, running on a network of PCs in the teaching laboratory.

The syllabus mirrors the recommended text book very closely. Other text-books are also listed below as sources of additional reading.

The course should be of interest to Computer Scientists and those following joint programmes (CS/Maths, CS/Stats). It is also suitable for Chemistry and Engineering students who are concerned with the application of high performance parallel computing for their particular field of study e.g. Simulation of chemical Behaviour.

High Performance Computing

Summary:

Laboratory work will be based on the MPI (Message Passing Interfaces) standard, running on a network of PCs in the teaching laboratory.

The syllabus mirrors the recommended text book very closely. Other text-books are also listed below as sources of additional reading.

Credits:
15.0
Pre-requisites:
Some prior knowledge of networking and operating systems or similar, or by prior agreement of the module leader.
Aims:
To introduce students to the paradigm of Parallel Computing, an awareness of its advantages and current limitations and allow the development of practical programming skills in a parallel computing environment
Objectives:
Students will gain an understanding and practical knowledge of:

Introduction to parallel computers,
Introduction to message-passing systems,
Introduction to parallel programming strategies,
Methods for load balancing,
Issues surrounding shared memory programming,
An examination of parallel processing for numerical (e.g. parallel sorting) and image processing.

Core Skills:
Technical report writing and presentaion, writing skills
Books:

Recomended Texts

Parallel Programming , Wilkinson and Allen; 2nd. Ed. ISBN 0-13-140563-2, 2005, Pearson/Prentice Hall.

Additional Reading Material

1. An Introduction to Parallel Computing: Design & Analysis of Algorithms, 2nd. Ed , Grama et al., ISBN 020 164 8652

2. Parallel Programming: An Introduction , Thomas Braunl (Prentice Hall)

3. Advanced Computer Architectures, A Design Space Aproach , D Sima, T Fountain and P Kacsuk (Addison-Wesley 1997)

4. Parallel Computing 2 , Hockney and Jesshope (Adam HilgerLtd)

5. Introduction to Parallel Computing , Ted G Lewis and Hesham El-Rewini (Prentice Hall 1992)

6. Parallel Computing, theory and practice , Michael J Quinn(McGraw-Hill, Inc. 1994)

Mobile Services

Basic mobile services for computer and communication resource poor environments that are accessed over a wireless network and independent of specific devices and platforms are first considered before this model is extended to the realm of ubiquitous or pervasive computing to include context-aware interaction, automated sensing and capture, the disappearing computer and ambient intelligence.

Mobile Services

Summary:
Basic mobile services for computer and communication resource poor environments that are accessed over a wireless network and independent of specific devices and platforms are first considered before this model is extended to the realm of ubiquitous or pervasive computing to include context-aware interaction, automated sensing and capture, the disappearing computer and ambient intelligence.
Credits:
15.0
Pre-requisites:
ELEM002 or ELEM039
Aims:
To enable students to: Understand the characteristics, motivation and opportunities for developing mobile user services Appreciate the strengths and weaknesses of developing mobile services using different software architectures. Understand the development process for creating and maintaining mobile services Understand the e-commerce and management issues associated with rapid development and deployment of mobile services
Objectives:
Describe the basic principles of mobile services Identify the basic components of mobile services and explain how they work Explain the key issues associated with constructing mobile services and the main approaches taken to developing such services. Design and create an application using contemporary middleware Explain the main application areas for mobile services.
Core Skills:
Analyse requirements and design a system (from assignment). Create a well-written report.
Books:
Poslad S. (2009) Ubiquitous Computing: Smart Devices, Environments and Interaction, Wiley, ISBN-13 9780470035603

Security and Authentication

The course is concerned with the principles and practice used for secure communications in the Internet.

Security and Authentication

Summary:
The course is concerned with the principles and practice used for secure communications in the Internet.
Credits:
15.0
Aims:
The course aims to give students an introduction to the principles and practice of cryptography and authentication used for network security.
Objectives:
Describe the principles of cryptography and its uses in the Internet. Describe the principles of public-key cryptography and its uses in the Internet. Explain message authentication and digital signatures. Explain the security protocols and methods used in the Internet

Entrepreneurship