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Item Details
Title: KALMAN FILTERING AND NEURAL NETWORKS
By: Simon S. Haykin
Format: Hardback

List price: £140.95


We currently do not stock this item, please contact the publisher directly for further information.

ISBN 10: 0471369985
ISBN 13: 9780471369981
Publisher: JOHN WILEY & SONS INC
Pub. date: 8 October, 2001
Series: Adaptive and Learning Systems for Signal Processing, Communications and
Pages: 304
Description: Kalman filtering is a well-established topic in the field of control and signal processing and represents by far the most refined method for the design of neural networks. This book takes a nontraditional nonlinear approach and reflects the fact that most practical applications are nonlinear.
Synopsis: State-of-the-art coverage of Kalman filter methods for the design of neural networks This self-contained book consists of seven chapters by expert contributors that discuss Kalman filtering as applied to the training and use of neural networks. Although the traditional approach to the subject is almost always linear, this book recognizes and deals with the fact that real problems are most often nonlinear. The first chapter offers an introductory treatment of Kalman filters with an emphasis on basic Kalman filter theory, Rauch-Tung-Striebel smoother, and the extended Kalman filter.Other chapters cover:* An algorithm for the training of feedforward and recurrent multilayered perceptrons, based on the decoupled extended Kalman filter (DEKF)* Applications of the DEKF learning algorithm to the study of image sequences and the dynamic reconstruction of chaotic processes* The dual estimation problem* Stochastic nonlinear dynamics: the expectation-maximization (EM) algorithm and the extended Kalman smoothing (EKS) algorithm* The unscented Kalman filter Each chapter, with the exception of the introduction, includes illustrative applications of the learning algorithms described here, some of which involve the use of simulated and real-life data. Kalman Filtering and Neural Networks serves as an expert resource for researchers in neural networks and nonlinear dynamical systems. An Instructor's Manual presenting detailed solutions to all the problems in the book is available upon request from the Wiley Makerting Department.
Illustrations: Ill.
Publication: US
Imprint: John Wiley & Sons Inc
Returns: Returnable
Some other items by this author:
ADAPTIVE FILTER THEORY (HB)
ADAPTIVE FILTER THEORY (PB)
ADAPTIVE RADAR SIGNAL PROCESSING (HB)
ADAPTIVE SIGNAL PROCESSING (HB)
AN INTRODUCTION TO ANALOG AND DIGITAL COMMUNICATIONS (HB)
AN INTRODUCTION TO ANALOG AND DIGITAL COMMUNICATIONS (HB)
COGNITIVE DYNAMIC SYSTEMS (HB)
COMMUNICATION SYSTEMS (PB)
CORRELATIVE LEARNING (HB)
DIGITAL COMMUNICATION SYSTEMS (HB)
DIGITAL COMMUNICATIONS (PB)
FUNDAMENTALS OF COGNITIVE RADIO (HB)
HANDBOOK ON ARRAY PROCESSING AND SENSOR NETWORKS (HB)
INTELLIGENT SIGNAL PROCESSING (HB)
INTRODUCTION TO DIGITAL AND ANALOG COMMUNICATIONS (HB)
KERNEL ADAPTIVE FILTERING (HB)
MULTIPLE-INPUT MULTIPLE-OUTPUT CHANNEL MODELS (HB)
NEURAL NETWORKS AND LEARNING MACHINES (PB)
NEW DIRECTIONS IN STATISTICAL SIGNAL PROCESSING (HB)
NONLINEAR FILTERS (HB)
NONLINEAR METHODS OF SPECTRAL ANALYSIS (PB)
RADAR ARRAY PROCESSING (PB)
REGULARIZED RADIAL BASIS FUNCTION NETWORKS (HB)
REMOTE SENSING OF SEA ICE AND ICEBERGS (HB)
SIGNALS AND SYSTEMS
SPACE-TIME LAYERED INFORMATION PROCESSING FOR WIRELESS COMMUNICATIONS (HB)
STATISTICAL COMMUNICATION THEORY (HB)
WILEYPLUS STAND ALONE TO ACCOMPANY AN INTRODUCTION TO ANALOG AND DIGITAL COMMUNICATIONS (PB)

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