Postgraduate Course: Advanced Coding Techniques (MSc) (PGEE11121)
Course Outline
| School | School of Engineering |
College | College of Science and Engineering |
| Course type | Standard |
Availability | Not available to visiting 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 cover the current topics of interest in Advanced Coding Techniques. In particular information theory fundamentals related to source coding and its extension to channel capacity are studied. Rate-distortion theory and quantisation for uncorrelated and correlated signals are of particular interest.
Syllabus:
1. Scalar quantisation,
2. Asymptotic quantisation theory,
3. Vector quantisation,
4. Rate-distortion theory,
5. Channel capacity evaluations.
Practical examples of the above concepts are presented throughout the course. |
Entry Requirements (not applicable to Visiting Students)
| Pre-requisites |
|
Co-requisites | |
| Prohibited Combinations | |
Other requirements | None |
| Additional Costs | None |
Course Delivery Information
|
| Delivery period: 2014/15 Semester 2, Not available to visiting students (SS1)
|
Learn enabled: Yes |
Quota: None |
|
Web Timetable |
Web Timetable |
| Course Start Date |
12/01/2015 |
| Breakdown of Learning and Teaching activities (Further Info) |
Total Hours:
100
(
Lecture Hours 33,
Programme Level Learning and Teaching Hours 2,
Directed Learning and Independent Learning Hours
65 )
|
| Additional Notes |
|
| Breakdown of Assessment Methods (Further Info) |
Written Exam
100 %,
Coursework
0 %,
Practical Exam
0 %
|
| Exam Information |
| Exam Diet |
Paper Name |
Hours & Minutes |
|
| Main Exam Diet S2 (April/May) | | 2:00 | |
Summary of Intended Learning Outcomes
| The students will understand fundamentals as well as advanced concepts in source coding. They will be able to quantify the bit rate that is theoretically needed to perform source coding of continuous-valued signals with some given maximum distortion. They will be able to explain the complexity-quality trade-offs in practical systems and they will be able to quantify how close practical quantisation algorithms can get to the theoretical limits given by information theory. They will be able to design scalar and vector quantisers for practical signals. They will also understand how information theory can be used to predict the data capacity of communications channels. |
Assessment Information
| 100% Examination |
Special Arrangements
| None |
Additional Information
| Academic description |
Not entered |
| Syllabus |
Not entered |
| Transferable skills |
Not entered |
| Reading list |
A. Gersho and R. M. Gray, Vector Quantization and Signal Compression. Kluwer Academic Publishers, 8th ed., 2001.
T. Cover and J. Thomas, Elements of Information Theory. John Wiley & Sons, Inc., 1991. |
| Study Abroad |
Not entered |
| Study Pattern |
Not entered |
| Keywords | Not entered |
Contacts
| Course organiser | Dr John Thompson
Tel: (0131 6)50 5585
Email: John.Thompson@ed.ac.uk |
Course secretary | Mrs Sharon Potter
Tel: (0131 6)51 7079
Email: Sharon.Potter@ed.ac.uk |
|
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