Postgraduate Course: Advanced Concepts in Signal Processing (PGEE11020)
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 |
|
|
| Course description |
This course aims to introduce techniques for performing pattern recognition, classification and adaption in the analysis of complex signals and data sets.
Introduction to Pattern Recognition, Detection, Classification, Modelling. Statistical Inference, Cluster Analysis, Neural Networks, Latent Variable Models, Independent Component Analysis, Hidden Markov Models, Applications to Speech, Audio and Image Data
|
Course Delivery Information
|
| Delivery period: 2010/11 Semester 2, Available to all students (SV1)
|
WebCT enabled: Yes |
Quota: None |
| Location |
Activity |
Description |
Weeks |
Monday |
Tuesday |
Wednesday |
Thursday |
Friday |
| King's Buildings | Lecture | | 1-11 | | | | 09:00 - 10:50 | | | King's Buildings | Tutorial | | 1-11 | | | | 11:10 - 12:00 | |
| First Class |
First class information not currently available |
Summary of Intended Learning Outcomes
Students will acquire an understanding of pattern recognition and adaptive methods and will learn how to apply these methods to the processing of a broad class of signals.
By the end of the module the student will be able to: Recall a range of techniques and algorithms for pattern recognition and intelligent processing of signals and data, including neural networks and statistical methods. Derive and analyse properties of these methods. Discuss the relative merits of different techniques and approaches. Implement some of these techniques in software (e.g. Matlab). Apply these methods to the analysis of signals and data.
|
Assessment Information
| 100% closed-book formal written examination |
| Please see Visiting Student Prospectus website for Visiting Student Assessment information |
Special Arrangements
| Not entered |
Contacts
| Course organiser |
Dr Michael Davies
Tel:
Email: mike.davies@ed.ac.uk |
Course secretary |
Mrs Kim Orsi
Tel: (0131 6)50 5687
Email: Kim.Orsi@ed.ac.uk |
|
copyright 2010 The University of Edinburgh -
1 September 2010 6:25 am
|
University Homepage