Recent developments in signal processing have made it clear that significant performance gains can be achieved beyond those achievable using standard adaptive filtering approaches. Adaptive Signal Processing presents the next generation of algorithms that will produce these desired results, with an emphasis on important applications and theoretical advancements. It is rapidly becoming one of the most effective techniques for reducing computational complexity and improving the convergence rate of algorithms in signal processing applications.

This course provides an introductory, yet extensive guide on the theory of various adaptive filtering techniques. The course leader will discuss the basic principles that underline the design and implementation of adaptive signal processing. This course bridges the gaps between the mixed–domain natures of subband adaptive filtering techniques and provides enough depth to the material augmented by many MATLAB® functions and examples.

Adaptive Signal Processing is an invaluable tool for graduate students, researchers, technical managers, computer scientists and practitioners working in the areas of signal processing, communications, controls, radar, sonar, and biomedical engineering.
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