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

Preface.

Acknowledgments.

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.