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Have you ever wondered how complex digital systems, such as those in telecommunications, multimedia, transportation, aerospace etc, can perform so many impressive functionalities? The core devices within these complex systems are based on Embedded Systems that are designed and dedicated to perform specific operations.
The widespread use and deployment of embedded systems in a broad range of electronic and communication engineering systems has exhibited an unprecedented expansion in the last few years. The combination of Embedded Systems with Signal Processing and Multimedia Communications is a prime technology in the on-going evolution of modern high-tech electronic equipment and its application products. Due to tremendous growth in consumer electronics, industries related to wireless communications, signal/image processing, machine intelligence, and internet, are actively recruiting skilled engineers with an in-depth working knowledge of embedded systems to support their development of next generation advanced competitive technology.
This exciting new MSc (masters) course, developed with the support of industry, integrates academic study and the realisation of embedded systems with emphasis and applications on multimedia communications and signal processing. The course is offered on the campus of Brunel University in London, UK. As a student attending Brunel University London's Embedded Systems course, you will study the fundamentals of embedded systems combined with extensive practical and hands-on work on embedded systems design, modelling and implementation. The course offers you the opportunity to explore embedded systems applications, namely, communications, multimedia, signal processing, and intelligent systems, through a set of carefully designed application-based modules that combine theory and application..
The course satisfies both the current and the future demands of advanced information technology industries internationally. Such research and development demands are met through the training and education of skilled engineers with advanced knowledge of embedded systems technology and its applications on multimedia communications and signal processing. Brunel University offers an exciting opportunity for study in this advanced technological area. Studying towards Brunel University Londons Embedded Systems degree will equip your career with the excellent international reputation of Brunel University London in engineering education.
About Electronic and Computer Engineering at Brunel
The Electronic and Computer Engineering discipline is one of the largest in the University, with a portfolio of research contracts totalling £7.5 million, and has strong links with industry.
We have a wide range of research groups, each with a complement of academics and research staff and students. The groups are:
* Media Communications
* Wireless Networks and Communications
* Power Systems
* Electronic Systems
* Sensors and Instrumentation
The laboratories are well equipped with an excellent range of facilities to support the research work and courses. We have comprehensive computing resources in addition to those offered centrally by the University. The discipline is particularly fortunate in having extensive gifts of software and hardware to enable it to undertake far-reaching design projects.
The Women in Engineering Scholarship is available for students on this course.
The main aim of this course is to endow graduates with advanced knowledge and transferable skills in the design, modelling, implementation and evaluation of embedded systems for signal processing and multimedia communications, such that they can contribute effectively to the increasingly complex and rapidly evolving technologies that are prevalent in the industry or research.
Specific aims of this course are to:
* Provide advanced knowledge and skills relevant to the theory and best practise of modern embedded systems technology (including FPGA and DSP) and its applications on multimedia signal processing and communications.
* Develop transferable skills in design, modelling, implementation, and evaluation of embedded systems for signal processing and multimedia communications that are contributable in either industry or academic employment.
* Develop the ability of analysing complex technical problems, and the versatility to apply embedded systems technology across a range of engineering areas with emphasis on multimedia signal processing and communications.
* Develop innovation, creativity and independent learning ability required for continuing professional development, further research, and for acquiring new skills at a high level.
The course equips graduates with the knowledge and skills to enter a demanding and competitive job market, and also provides graduates the necessary skills, abilities and confidence to embark on a doctoral programme.
The following modules will be taught:
* Embedded Systems Hardware
Introduces and promotes the understanding of the utilisation and principles of reconfigurable computing.
* Advanced Signal Processing (core for signal processing pathway)
Covers a broad range of the theory and applications of advanced digital signal processing (DSP) that is pervasive in some of the most useful communication and signal processing systems such as radar, mobile phones, medical signal processing etc.
* Advanced Digital Communications (core for multimedia communications pathway)
Aims to teach students advanced topics in digital communication systems, such as multicarrier digital transmission and multiple access techniques, as well as associated case studies.
* DSP for communications
This module focuses on the real-time implementation of key DSP algorithms used in modern electronic and communication systems.
* Embedded Systems Engineering
This module aims to provide detailed knowledge of real-time computing for advanced embedded and control computer systems. The module will promote the understanding of the various engineering, scientific and economic tradeoffs necessary in the design of advanced embedded systems.
* Advanced Multimedia Processing
Addresses advanced methods and algorithms in multimedia signal processing aimed at representing, indexing, compressing and delivering audiovisual streams over networked environments. In-depth coverage of Audio/speech processing, Image/video processing, and Multimedia data processing.
* Embedded Intelligent Systems
Explores the goals and methods of Artificial Intelligence (AI) from its inception to the present day. The emphasis is on a how we can make the machine do intelligent signal processing, such as adaptive filtering, channel optimisation, data classification, and data mining.
* Wireless Network and Multimedia Technologies
Introduces the students in the design and operation of wireless networks through concepts, terminologies and standards.
* Project Management
To main aim of the module is to give students a comprehensive understanding and critical awareness of the latest advanced techniques and strategies for Project Management, including management tools, management and reporting methods and team building.
* Dissertation project
The dissertation project is a stimulating and challenging part of the MSc programme. Dissertations may be carried out on any approved topic related to embedded systems technologies and their applications. Essentially the dissertation gives the student the opportunity to apply the knowledge and skills taught in the programme to a topic of their own interest, of interest to a sponsoring or industrial organisation, or of research interest.
Representative project/workshops are in the areas below (but not limited to these areas):
* Signal processing of biomedical signal, such as ECG, EEG
* Filtering of radio signals, low and high pass filtering
* Signal processing of medical imaging modalities
* Filter design, conversion from analogue to discrete filters
* Video surveillance and biometrics
* 3D conferencing
* Image and radar avoidance systems for cars
* Embedded systems used in inter-car communication and avoidance systems
* Health monitoring/performance applications
* Assisted living applications
* Sports signal processing
* Multi-layer structure analysis from Terahertz data
* Fast sampling of ultra-wideband signals