BEng (Hons) Micro Electronics
Course Modules
ENRTA3065 - Digital Signal Processing
ENRTA3066 - Artificial Intelligence
ENRTA3067 - Electronic Devices & Programmable Systems
ENRTA3068 - Digital Image Processing
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Faculty of Technology and Environment
School of Engineering
Introduction to the course
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The Course Modules and their credits
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Your Programme Leader for this course in Micro Electronics is Dr Mike Shaw (Email: M.M.Shaw@ljmu.ac.uk), please contact him if you require further information.
Dr Mike Shaw is Deputy Director of the School of Engineering and Faculty Head of International & Collaborative Programmes. He has always had a professional involvement in Electronic Engineering, working for a number of years as a Radio & Electronics Officer with British Petroleum, and subsequently as an Engineer with Marconi Space & Defence Systems before joining what was then, Liverpool Polytechnic. Having joined the institution, initially on a part-time basis in 1986, Mike has had a number of jobs ranging from Senior Lecturer, Principal Lecturer and Director of the Centre for Precision Measurement and Industrial Inspection, and his current role as Deputy Director of the School of Engineering. During this time, he developed his research interests in high precision, optical non-contact measurement. He was latterly Faculty Head of Quality before moving to his current position as Faculty Head of International & Collaborative Programmes.
Mike has always maintained a strong interest in his profession, particularly through the Institution of Electrical Engineers (IEE), or what is now known as the Institution of Engineering & Technology (IET), of which he is a Fellow, and as well as serving on the Council of the IEE, he was their Branch Chairman between 1999 - 2001.
Mike maintains his professional interests as director of the Rotary International project, The Excitement of Science. Run in conjunction with the Royal Institution in London, in the world famous Faraday Theatre, the project aims to raise the profile of science and engineering, by firing the imagination and enthusiasm, particularly of young people, in the way that only well conducted, participative and presented science can do.
ENRTA3065 - Digital Signal Processing
Module Leader
Dr Munther Gdeisat
Senior Lecturer in Digital Systems
General Engineering Research Institute
James Parsons Building
Email: m.a.gdeisat@ljmu.ac.uk
Dr. Munther Gdeisat is a Senior Lecturer in Digital Signal Processing at Liverpool John Moores University (LJMU). He received his BEng in Communications Engineering from Yarmouk University-Jordan in 1994. He was awarded his PhD in image processing from Liverpool John Moores University in 2000. To continue his research, the General Engineering Research Institute (GERI-LJMU) has appointed him as a postdoctoral research for two years. Dr. Gdeisat worked in Hertfordshire University as Senior Lecturer in Digital Systems for two years. Then he returned back to GERI to continue his research in image processing, fringe pattern analysis, phase unwrapping and wavelet transform. He published more than 15 papers in international journals conferences.
Introduction
This module builds on the level two module in maths, signal processing and simulation to provide an extensive knowledge of Digital Signal Processing and includes:
- Understand structures of digital signal processing systems
- Design finite impulse response filters
- Design infinite impulse response filters
- Apply transforms to solve digital signal processing problems and spectral estimation
- Apply digital signal processing to a range of real industrial problems.
Aims
This module is intended to provide students with a good appreciation of the mathematical concepts necessary to apply digital signal processing algorithms to a range of engineering problems.
Learning Outcomes
After completing the module the student should be able to:
1 Specify and design DSP Systems
2 Design FIR Filters
3 Design IIR Filters
4 Solve DSP problems and estimate spectra using appropriate transforms.
5 Apply DSP to a range of applications.
Outline Syllabus
Architecture requirements of DSPs,
Use of MATLAB & SIMULINK
FIR filter design: The choice of windows: fixed form v. adaptable form, Design of optimal filters
IIR filter design: analogue prototypes: Butterworth, Chebyshev, Elliptic. Bilinear transform.
Use of transforms in one of two dimensions: Fourier, Laplace, Z, Discrete Cosine Transform.
Non-parametric methods of spectral estimation, bias, resolution, Wavelets.
DSP systems applied to speech and image processing.
The module is assessment is divided into two elements: experimental and theoretical. The experimental part consists of three lab test in digital signal processing using Matlab and Simulink. The marks for the lab tests are 10%, 15%, and 25%. The theoretical part is assessed in two hours exam at the end of the module and worth 50%.
Indicative References
Ifeacher E.C., Jervis B.W. (2002) 'Digital Signal Processing: A practical Approach' 2nd Addison-Wesley 0 201 59619-9
Mitra, S.K (1998) 'Digital Signal Processing :A Computer-Based Approach' McGraw-Hill International Editions 0-07-115793-X
Oppenheim A.V., Oppenheim A.V., Buck J. R. (1999) 'Discrete-Time Signal Processing' Prentice Hall 0137549202
ENRTA3066 - Artificial Intelligence
Module Leader
Dr Karl Jones
Principal Lecturer
Engineering
James Parsons Building
Email: k.o.jones@ljmu.ac.uk
Dr. Karl Jones is a Principal Lecturer in at Liverpool John Moores University (LJMU). He received his BEng (Hons) in Electrical and Electronic Engineering in 1988. He was awarded his PhD in Fermentation Control Systems in 1995. His current research interests include the application of Artificial Intelligence and Evolutionary Computing to biotechnological processes and Control Systems. He is also investigating approaches to Education in Engineering. He has published over 80 papers in books, journals, and conferences; he also organises a number of international conferences.
Introduction
A range of artificial intelligence (AI) techniques will be studied. Case studies will illustrate the application of AI to engineering problems. Students will gain hands on use of implementing AI methods using computer software packages and includes:
- Understanding of artificial intelligence and knowledge based systems
- Neural networks, multi-layer perceptron and back propagation
- Genetic algorithms, optimisation, mutation and evolution techniques
- Case study illustrations
Aims
To provide an introduction to a range of artificial intelligence (AI) techniques and how they can be applied to engineering and technological problems.
After completing the module the student should be able to:
1 Design and apply AI and knowledge based systems to engineering applications.
2 Develop and evaluate a neural network application.
3 Appreciate optimization problems and their solution with genetic algorithms.
Introduction to AI including definitions.
Knowledge based systems: knowledge acquisition and representation, construction, operation, forward and backward chaining.
Neural nets: overview of network architectures and learning schemes, perceptron learning, multi-layer perceptron and backpropagation, implementation.
Genetic algorithms: optimisation and conventional techniques, data coding, reproduction, cross-over, mutation and evolution techniques.
Case studies will illustrate the application and performance of AI methods in engineering, e.g. modelling of systems and signals; pattern recognition; image processing.
Indicative References
Negnevitsky, M (2004) 'Artificial Intelligence: A Guide to Intelligent Systems' 3rd Edition Addison Wesley 0321204662
T Dean, J Allen & Y Aloimonos. (1995) 'Artificial intelligence: theory and practice' The Benjamin / Cummings Publishing Co.
P Picton (2000) 'Neural networks' 2nd edition Palgrave 0-333-80287
R Beale & T Jackson (1990) 'Neural computing: an introduction' IOP Publishing Ltd. 0852742622
MATLAB and Neural Networks Toolbox.
ENRTA3067 - Electronic Devices & Programmable Systems
Module Leader
Professor Jian Zhang
Professor of Microelectronics
Engineering
James Parsons Building
Email: j.f.zhang@ljmu.ac.uk
Jian Zhang received Ph.D degree from the University of Liverpool in 1987. From 1986 to 1992, he was a post-doctoral research assistant at the University of Liverpool. In 1992, he joined Liverpool John Moores University and became a Professor in 2001. His current teaching and research interests are in the area of VLSI devices, fabrication and testing. He was a member of the technical program committee for the IEEE Semiconductor Interface Specialist Conference (SISC), held annually in USA, and a co-organiser for the International Symposium on Silicon Nitride, Silicon Dioxide and Other Emerging Thin Insulating Films, held at the Electrochemical Society Meeting. He has delivered invited talks at several international conferences and research seminars at many external organisations. He is also invited to deliver short courses organized by UK government to train employees of microelectronic companies.
TUTOR
Dr Weidong Zhang
Senior Lecturer
Engineering
James Parsons Building
Email: W.Zhang@ljmu.ac.uk
Dr. Wei D. Zhang received the B.sc degree in semiconductor physics and devices from the Beijing Institute of Technology in 1989, the M.sc degree in semiconductor devices and microelectronics from the Xidian University in 1992, and the PhD degree in microelectronics from the Liverpool John Moores University in 2003. From 1992 to 1999, he was a Lecturer and then an Associated Professor at the Xidian University. He became a Lecturer at the Bournemouth University in 2002, and joined Liverpool John Moores University as a Senior Lecturer in 2005. His research interests cover the area of reliability of MOS devices, the degradation and breakdown of oxide dielectrics, and VLSI design.
Introduction
This module will provide undergraduates with a comprehensive understanding of state-of-the-art electronic devices and systems used in the present industrial and consumer products. It will also foster the awareness of students in the future challenges and opportunities in the microelectronics industry and help the student to:
- Appreciate and understand modern electronic device structures and systems
- Recognise future challenge and opportunity in such a rapidly changing industry
- Propose appropriate modern design structures
- Design using CPLD, FPGA and reconfigurable architectures, and test methodologies
- Confidently use a proprietary CAD design tool such as Xilinx
Aims
This module will give students knowledge and experience of designing using state of the art integrated circuit technologies and devices.
Learning Outcomes
After completing the module the student should be able to:
1 Demonstrate knowledge of modern electronic devices and systems
2 Analyse the performance of advanced devices and systems
3 Select components and systems for engineering applications
4 Recognize the future challenge and opportunity in this rapidly changing area
5 Propose the most appropriate modern design structures for particular applications.
6 Design using modern CPLD, FPGA and reconfigurable architectures.
7 Confidently use a proprietary CAD tool such as Xilinx, to design, test and fabricate a complex digital system.
8 Incorporate industry standard test methodologies into designs.
Outline Syllabus
A Review of microelectronic devices within industry: How did it happen?
Flash memories: structures, programming, erasing, reading, endurance and data retention.
TFTs and LCDs: Amorphous-Si TFTs and Poly-Si TFTs; Passively addressed LCDs and actively addressed LCDs
Voltage controlled oscillators (VCOs) and Phase Locked Loops, AM and FM Modulation and De-Modulation
Nano-meter transistors: challenges and opportunities
Future of microelectronic and computer industries: International Roadmap
Review of programmable architectures: PROM, PLD, EPLD, PAL, GAL, CLB, CPLD & FPGA. Design using reconfigurable systems. Combinational, synchronous and asynchronous sequential design in programmable logic. Considerations for high speed systems, metastability and clock distribution, transmission line considerations. Design, test, simulation and implementation using a proprietary CAD tool such as Xilinx. Design for testability and reliability, JTAG Boundary Scan (IEEE 1149.1), BIST methods, in-circuit testing, scan path method.
Assessment
Assessment of the module is by a 2 hour examination (50%) for the device section and by a project (50%) for the programmable system section. There are four questions with equal marks in the examination paper and you can choose any three of them. The project is a practical digital design assignment using Xilinx ISE software and Spartan3 development board. Students are required to analyse the design requirements; carry out the design, simulation and verification; implement the design into FPGA, and demonstrate the results to the tutor. A formal project report should be submitted for assessment before the deadline.Indicative References
Muller R.S., Kamins T.I., and Ko P.K (2003) 'Device Electronics for Integrated Circuits' Wiley 0471593982
Chang, C.Y. and Sze, S.M. (1996) 'VLSI Technology' McGraw-Hill 0-07-114105-7
Yang, E.S. (1998) 'Microelectric Devices' McGraw-Hill 0-07-072238-2
Wakerly, JF (2000) 'Digital Design, Principles & Practices,' 3rd Ed Prentice-Hall.
Roth, CH, (2004) 'Fundamentals of Logic Design' 5th Ed Brooks/Cole Publishing Xilinx materials on www.xilinx.co.uk/ '
Oldfield, JV, Dorf, RC, (1995) 'Field Programmable Gate Arrays: Reconfigurable Logic for Rapid Prototyping and Implementation of Digital Systems' Wiley
ENRTA3068 - Digital Image Processing
Module Leader
Dr Rebecca Bartlett
Engineering
James Parsons Building
Email: r.bartlett@ljmu.ac.uk
Dr Rebecca Bartlett is a principal lecturer in the School of Engineering at Liverpool John Moores University. She received a BSc(hons) in Physics with Electronics and Instrumentation from the University of Leeds in 1990, and subsequently worked for British Aerospace developing avionics systems for commercial aircraft. She was awarded a PhD in 1998 by the University of Manchester for work imaging hydraulic seals in situ. She has published research into plastic optical fibre sensors for environmental applications and is currently researching Education in Engineering, all in collaboration with a number of other European Institutions.
Introduction
This module will provide students with a sound grasp of the basic theory and applications of modern digital image processing and includes:
- Representation and structure of digital images
- Optical basis of image formation
- Spatial filtering and frequency domain operations on images
- Morphology, segmentation and object labelling
- Colour images, image compression techniques and digital image processing applications
Aims
To introduce the student to the basic principles of digital image processing for the enhancement of images and for the extraction of meaningful information from them with applications in engineering.
Learning Outcomes
After completing the module the student should be able to:
1 Analyse digital images and their uses
2 Apply the theory and implementation of a range of basic image processing operations
3 Determine the applications, advantages and disadvantages of a range of basic image processing functions.
4 Analyse the advantages and disadvantages of image compression techniques
5 Specify the most appropriate image processing techniques for a particular application
Outline Syllabus
Background: digital image representation, sampling and quantization, image storage
Optical basis of image formation: imaging geometry, stereo-vision, the human visual system.
The basic principles and applications of:
- Point processing and histogram manipulation,
- Spatial filtering: smoothing, high-pass filtering, first and second derivative filters.
- Frequency domain operations: Fourier transform, ideal low and high pass filters, Butterworth filter,
- Morphology, segmentation and object labeling.
Introduction to colour images.
Image compression: Lossy and non-lossy compression.
Applications of digital image processing.
Indicative References
Gonzalez R.C. and Woods R.E. (2002) 'Digital Image Processing' Prentice Hall 0201180758
Castleman K.R. (1996) 'Image Processing' Prentice Hall 0132114674
Gonzalez, R.C, Woods, R.E., and Eddins, S.L (2004) 'Digital Image Processing Using MATLAB' Pearson Prentice Hall 013008519-7
