Module overview
This module aims to introduce to the students signal processing techniques, including analogue and digital filter design and systems design theories. The module also introduces the concepts of statistical signal processing including estimation and detection theories, with illustrative case studies to demonstrate how these techniques can be used in communications systems.
The module uses the specialist computation/simulation tool Matlab.
Aims and Objectives
Learning Outcomes
Subject Specific Intellectual and Research Skills
Having successfully completed this module you will be able to:
- Characterise random signals and processes
- Analyse the effect of sampling on electronics signals
- Apply statistical signal processing estimation techniques to communications systems
Subject Specific Practical Skills
Having successfully completed this module you will be able to:
- Design analogue and digital filters according to set specifications
- Design adaptive filters
Syllabus
Analog filter design
- Specifications, physical approximations, performance specifications, design.
- Covering Butterworth, Chebyshev, Elliptic types and their relative performance
Sampling and reconstruction theory
- Review of the basics
- z transform analysis
Digital filter design
- Specifications, physical approximations, performance specifications, design.
- Covering Butterworth, Chebyshev, Elliptic types and their relative performance.
Random processes
- Models and processing
Adaptive filter design and implementation
Estimation Theory
- Maximum Likelihood Estimation, Least squares estimation, Baysian estimation
Learning and Teaching
| Type | Hours |
|---|---|
| Preparation for scheduled sessions | 18 |
| Follow-up work | 18 |
| Lecture | 36 |
| Tutorial | 12 |
| Wider reading or practice | 46 |
| Completion of assessment task | 10 |
| Revision | 10 |
| Total study time | 150 |
Resources & Reading list
Textbooks
A. V. Oppenheim , A. S. Willsky and S. H. Nawab (1996). Signals and Systems. Prentice Hall.
P. Denbigh (1998). System Analysis and Signal Processing. Addison-Wesley.
S.M. Kay (1993). Fundamentals of Statistical Signal Processing: Estimation Theory. New Jersey, USA: Prentice Hall, Upper Saddle River.
A. V. Oppenheim , R. W. Schafer and J. R. Back (1999). Discrete-time Digital Signal Processing. Prentice Hall Int.
M. J. Roberts (2003). Signals and Systems. McGraw Hill.
Assessment
Summative
This is how we’ll formally assess what you have learned in this module.
| Method | Percentage contribution |
|---|---|
| Examination | 90% |
| Coursework | 10% |
Referral
This is how we’ll assess you if you don’t meet the criteria to pass this module.
| Method | Percentage contribution |
|---|---|
| Examination | 100% |
Repeat
An internal repeat is where you take all of your modules again, including any you passed. An external repeat is where you only re-take the modules you failed.
| Method | Percentage contribution |
|---|---|
| Examination | 100% |
Repeat Information
Repeat type: Internal & External