Adaptive Filtering Primer with MATLAB

Discover the essential concepts of adaptive filtering with "Adaptive Filtering Primer with MATLAB" by Alexander D. Poularikas. Published by Taylor & Francis Ltd in 2017, this comprehensive guide spans 238 pages and is designed for both beginners and experienced practitioners in the field of signal processing.

This book delves into the fundamentals of adaptive filtering, featuring a wealth of examples and computer simulations to enhance understanding. Readers will explore critical topics such as discrete-time signal processing, random variables, stochastic processes, and the intricacies of the Wiener filter. Additionally, it covers the properties of the error surface, the steepest descent method, and the least mean square (LMS) algorithm, making it an invaluable resource for anyone looking to master adaptive filtering techniques.

Enhance your knowledge and skills in signal processing with this insightful primer, perfect for students and professionals alike.