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This book - Presents in simple terms the fundamentals of a complicated area of signal processing; Provides a self-contained, easily understood introduction to Wiener filtering, the LMS algorithm, and the least-squares approach; Demonstrates practical application through MATLAB programs and computer experiments; Includes abundant problems along with detailed solutions, hints, or suggestions for solving every problem in the book; Offers an appendix on matrix computation. Because of the wide use of adaptive filtering in digital signal processing and, because most of the modern electronic devices include some type of an adaptive filter, a text that brings forth the fundamentals of this field was necessary. The material and the principles presented in this book are easily accessible to engineers, scientists, and students who would like to learn the fundamentals of this field and have a background at the bachelor level. 'Adaptive filtering primer with MATLAB' clearly explains the fundamentals of adaptive filtering supported by numerous examples and computer simulations. The authors introduce discrete-time signal processing, random variables and stochastic processes, the Wiener filter, properties of the error surface, the steepest descent method, and the least mean square (LMS) algorithm. They also supply many MATLAB functions and m-files along with computer experiments to illustrate how to apply the concepts to real-world problems. The book includes problems along with hints, suggestions, and solutions for solving them. An appendix on matrix computations completes the self-contained coverage.