▪ To develop higher level signal processing techniques and apply them to some problems.
▪ To develop FIR adaptive filters and demonstrate their applications.
Knowledge and Understanding
On successful completion of this module the student should have:
▪ appreciation of the concepts of time and frequency domain descriptions of signals.
▪ appreciation of 'fixed' filter choices for noise reduction for different types of noise and signals.
▪ appreciation of correlations, linear prediction and matched filtering.
▪ appreciation of optimum filters and Wiener filters in particular, and their applications.
▪ appreciation of FIR adaptive filters and their applications.
▪ some knowledge of Kalman filters.
On successful completion of this module the student should be:
▪ knowledgeable about some signal processing techniques and their applications.
▪ knowledgeable about adaptive filters and their applications.
On successful completion of this module the student should:
▪ have the ability to apply an appropriate signal processing technique to a given problem.
▪ be able to apply the appropriate adaptive filter.
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.