Fundamentals of Adaptive Filtering

This book is based on a graduate level course offered by the author at UCLA and has been classed tested there and at other universities over a number of years. This will be the most comprehensive book on the market today providing instructors a wide choice in designing their courses.

• Offers computer problems to illustrate real life applications for students and professionals alike
• There will be an Instructor's Manual presenting detailed solutions to all the problems in the book

Contents

• Notation
• Symbols
• Optimal Estimation
• Linear Estimation
• Constrained Linear Estimation
• Steepest-Descent Algorithms
• Stochastic-Gradient Algorithms
• Steady-State Performance of Adaptive Filters
• Tracking Performance of Adaptive Filters
• Finite Precision Effects
• Transient Performance of Adaptive Filters
• Block Adaptive Filters
• The Least-Squares Criterion
• Recursive Least-Squares
• RLS Array Algorithms
• Fast Fixed-Order Filters
• Lattice Filters
• Laguerre Adaptive Filters
• Robust Adaptive Filters
• Bibliography
• Author Index
• Subject Index