Aims and Fit of Module

▪ To develop higher level signal processing techniques and apply them to some problems.
▪ To develop FIR adaptive filters and demonstrate their applications.

Learning outcomes

A. Demonstrate fundamental knowledge of random signals and their statistical characteristics in both time and frequency domain. B. Demonstrate critical understanding of statistical signal modeling and spectrum estimation. C. Design optimal detectors and analyse their performance in some practical applications. D. Develop optimum linear filter (Wiener filter) for signal estimation problems, and analyse the estimation error.

Method of teaching and learning

This module will be delivered through a combination of formal lectures, tutorials and supervised laboratory sessions.
Coursework is not normally anonymously marked as staff wish to provide meaningful feedback.