Postgraduate Course: Adaptive Signal Processing (PGEE11019)
Course Outline
| School | School of Engineering |
College | College of Science and Engineering |
| Course type | Standard |
Availability | Available to all students |
| Credit level (Normal year taken) | SCQF Level 11 (Postgraduate) |
Credits | 10 |
| Home subject area | Postgrad (School of Engineering) |
Other subject area | None |
| Course website |
None |
Taught in Gaelic? | No |
| Course description | This course will deal with the theory and applications of advanced signal processing topics, in particular modern spectral analysis, spectral estimation techniques and signal detection and the theory of adaptive filters and their applications.
Algorithms and structures for optimal linear filters: Optimum IIR filters, Inverse filtering and deconvolution, channel equalisation, matched and eigen-filters, Kalman filter; Adaptive Filters: Principles, Methods of Steepest descent, Recursive Least Squares based methods, Fast RLS methods, Performance Measures; Applications of Adaptive Filters: Adaptive Equalisation, Adaptive Noise Cancelling, Prediction; Modern Spectral Analysis: AR Spectral analysis, LPC, MV spectral analysis; Array Fundamentals: Beamforming, Optimum Array processing, Adaptive Beamforming
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Entry Requirements (not applicable to Visiting Students)
| Pre-requisites |
It is RECOMMENDED that students have passed
Statistical Signal Processing (PGEE11027) AND
Discrete-Time Signal Analysis (PGEE11026)
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Co-requisites | |
| Prohibited Combinations | |
Other requirements | None |
| Additional Costs | Compulsory book purchase: B. Mulgrew, P.M. Grant, and J.S. Thompson, Digital Signal Processing: Concepts and Applications (2nd Ed), Palgrave, 2003 |
Information for Visiting Students
| Pre-requisites | None |
| Displayed in Visiting Students Prospectus? | Yes |
Course Delivery Information
| Not being delivered |
Summary of Intended Learning Outcomes
| The students should understand the foundations of modern signal processing methods such as spectral analysis and estimation as well as adaptive filters. They should also be able to understand practical applications of these concepts and their limitations. |
Assessment Information
| 100% closed-book formal written examination |
Special Arrangements
| None |
Additional Information
| Academic description |
Not entered |
| Syllabus |
Not entered |
| Transferable skills |
Not entered |
| Reading list |
Not entered |
| Study Abroad |
Not entered |
| Study Pattern |
Not entered |
| Keywords | spectral analysis, spectral estimation, signal detection, adaptive filters, least squares methods |
Contacts
| Course organiser | Prof Bernie Mulgrew
Tel: (0131 6)50 5580
Email: |
Course secretary | Mrs Sharon Potter
Tel: (0131 6)51 7079
Email: |
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