Includes bibliographical references (p. 758-774) and indexes.

Random variables -- Linear algebra -- Complex gradients -- Scalar-valued data -- Vector-valued data -- Linear estimation -- Normal equations -- Orthogonality principle -- Linear models -- Constrained estimation -- Kalman filter -- Steepest-descent technique -- Transient behavior -- LMS algorithm -- Normalized LMS algorithm -- Other LMS-type algorithms -- Affine projection algorithm -- RLS algorithm -- Mean-square performance -- Energy conservation -- Performance of LMS -- Performance of NLMS -- Performance of sign-error LMS -- Performance of RLS and other filters -- Nonstationary environments -- Tracking performance -- Transient performance -- Weighted energy conservation -- LMS with Gaussian regressers -- LMS with non-Gaussian regressors -- Data-normalized filters -- Block adaptive filters -- Transform domain adaptive filters -- Efficient block convolution -- Block and subband adaptive filters -- Least-squares methods -- Least-squares criterion -- Recursive least-squares -- Kalman filtering and RLS -- Order and time-update relations -- Array algorithms -- Norm and angle preservation -- Unitary transformations -- QR and inverse QR algorithms -- Fast RLS algorithms -- Hyperbolic rotations -- Fast array algorithm -- Regularized prediction problems -- Fast fixed-order filters -- Three basic estimation problems -- Lattice filter algorithms -- Error-feedback lattice filters -- Array lattice filters -- Indefinite least-squares -- Robust adaptive filters -- Robustness properties.

"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. This book will interest students, experts, practitioners and instructors."--BOOK JACKET.

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