Fundamentals of Adptive Filtering

Fundamentals of Adaptive Filtering by Ali H. Sayed is a comprehensive textbook for graduate-level students and professionals in electrical engineering and signal processing. The book provides a detailed and rigorous treatment of the theory, analysis, and application of adaptive filters.
Key Features of the Book 📚
• Comprehensive Coverage: The book covers a wide range of topics, including fundamental estimation theory, linear estimation, stochastic gradient algorithms like the LMS (Least Mean Squares) and RLS (Recursive Least Squares) algorithms, and more advanced topics like fast algorithms and array processing.
• Theoretical Foundation: Sayed’s approach is highly analytical, focusing on the underlying mathematical principles. It provides a solid theoretical foundation, emphasizing geometric constructions, linear algebraic concepts, and vector notation. This contrasts with other books that may be more focused on a “cookbook” of algorithms.
• Emphasis on Analysis: A significant portion of the book is dedicated to the detailed performance analysis of adaptive filters, including steady-state performance, tracking behavior, and finite-precision effects. Sayed introduces an energy balance relation as a key tool for this analysis.
• Practical Applications: While deeply theoretical, the book includes numerous computer problems and projects that illustrate real-life applications. It provides MATLAB® solutions for these projects, making it a valuable resource for both students and practitioners.
• Author’s Expertise: Ali H. Sayed is a distinguished professor and a renowned expert in adaptive systems and signal processing, with a long and established career at institutions like UCLA and EPFL. The book reflects his extensive research and teaching experience in the field.