Student will learn advanced signal processing methods, especially linear optimal filter design, adaptive filters, spectrum estimation, nonlinear filters and how to select proper methods for signal processing tasks at hand.
After completing the course, the student
- Is familiar with the most important advanced signal processingr generic problems: optimal design, convergence, recursiveness in time, spectrum estimation;
- Is able to start from the formulation of a problem formulation and utilize a number of typical algorithmic tools to derive the solution;
- Knows what are the most important algorithms for optimal and adaptive filters: LMS, NLMS,RLS etc.
- Acquires practice on simulating optimal and adaptive algorithms with given input data and extracting useful performance indices helpful in comparing various algorithms.
- Knows how to integrate an optimal or adaptive filter in a number of important applications: echo cancelation, noise cancellation, channel equalization etc.