Adaptive filtering is a topic of immense practical and theoretical value, having applications in areas ranging from digital and wireless communications to biomedical systems. Now, preserving the style and main features of the earlier award-winning publication, Fundamentals of Adaptive Filtering (2005 Terman Award), the author offers readers and instructors a concentrated, systematic, and up-to-date treatment of the subject in this valuable new book.
Adaptive Filters allows readers to gain a gradual and solid introduction to the subject, its applications to a variety of topical problems, existing limitations, and extensions of current theories. The book consists of eleven parts—each part containing a series of focused lectures and ending with bibliographic comments, problems, and computer projects with MATLAB® solutions available to all readers. Additional features include:
Numerous tables, figures, and projects
Special focus on geometric constructions, physical intuition, linear-algebraic concepts, and vector notation
Background material on random variables, linear algebra, and complex gradients collected in three introductory chapters
Complete solutions manual available for instructors
MATLAB® solutions available for all computer projects
Adaptive Filters offers a fresh, focused look at the subject in a manner that will entice students, challenge experts, and appeal to practitioners and instructors.
About the Author
Ali H. Sayed is Professor of Electrical Engineering at UCLA, where he established and directs the Adaptive Systems Laboratory. He is a Fellow of the IEEE for his contributions to adaptive filtering and estimation algorithms. His research has attracted several recognitions including the 2003 Kuwait Prize, 2005 Terman Award, and several IEEE Best Paper Awards.