Postgraduate Course: Digital Signal Processing Laboratory (MSc) (PGEE11108)
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 | Digital Signal Processing Laboratory |
Course Delivery Information
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Delivery period: 2012/13 Semester 1, Not available to visiting students (SS1)
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Learn enabled: Yes |
Quota: None |
Location |
Activity |
Description |
Weeks |
Monday |
Tuesday |
Wednesday |
Thursday |
Friday |
No Classes have been defined for this Course |
First Class |
First class information not currently available |
No Exam Information |
Summary of Intended Learning Outcomes
Students are required to formulate solutions to practical communications, signal and image processing problems and to code, debug and run these in MATLAB. Specific learning outcomes are:
1. Understanding of how to use MATAB to simulate and analyze signal and image processing algorithms.
2. Reinforce the practical understanding of the following courses, Discrete-Time Signal Analysis PGEE11026; Digital Communication Fundamentals PGEE11025; Statistical Signal Processing PGEE11027; Image Processing PGEE11021 through practical labs and marked assignments. |
Assessment Information
100% coursework: marked assignments |
Special Arrangements
None |
Additional Information
Academic description |
Not entered |
Syllabus |
The course will teach students to solve simple problems in the areas of communications and signal processing in a MATLAB environment. The course will reinforce material taught in the co-requisite courses and provide practical experience of signal processing implementation in preparation for the project.
Course contents:
1. Introduction to signal processing in MATLAB including: generating time domain signals; simulating continuous and sampled signals; calculating the DFT, its properties and implementation; power spectral density estimation.
2. Discrete Time signal Analysis assignment
3. Communications assignment
4. Image processing assignment
Course assignments ¿ example exercises could be: simulating an adaptive noise cancellation problem, estimating frequencies and noise power in a time domain signal, simulating a simple modulation / demodulation and detection scheme, etc. |
Transferable skills |
Not entered |
Reading list |
Online MATLAB resources and lecture notes for co-requisite courses. |
Study Abroad |
Not entered |
Study Pattern |
The course will consist of 10 supervised 3 hour labs plus at least 70 hours personal study and programming time. |
Keywords | Signal Processing, Communications, Image Processing |
Contacts
Course organiser | Dr Michael Davies
Tel:
Email: mike.davies@ed.ac.uk |
Course secretary | Mrs Sharon Mulvey
Tel: (0131 6)51 7076
Email: Sharon.Mulvey@ed.ac.uk |
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© Copyright 2012 The University of Edinburgh - 31 August 2012 4:26 am
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