Kalman Filtering and Neural Networks by Simon S. Haykin
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Kalman Filtering and Neural Networks
By Simon S. Haykin

Kalman Filtering and Neural Networks

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Format: Hardback

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Kalman Filtering and Neural Networks by Simon S. Haykin

Book Description

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.

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Book Details

ISBN: 9780471369981
ISBN-10: 0471369985
Format: Hardback
(245mm x 166mm x 23mm)
Pages: 304
Imprint: John Wiley & Sons Inc
Publisher: John Wiley & Sons Inc
Publish Date: 12-Oct-2001
Country of Publication: United States

Books By Author Simon S. Haykin

Adaptive Filter Theory by Simon S. Haykin Adaptive Filter Theory, Paperback (July 2013)

'Adaptive Filter Theory', is ideal for courses in adaptive filters. Haykin examines both the mathematical theory behind various linear adaptive filters and the elements of supervised multilayer perceptrons.

Digital Communication Systems by Simon S. Haykin Digital Communication Systems, Hardback (April 2013)

Offers the most complete, up-to-date coverage available on the principles of digital communications. Focuses on basic issues, relating theory to practice wherever possible. Numerous examples, worked out in detail, have been included to help the reader develop an intuitive grasp of the theory.

Cognitive Dynamic Systems by Simon S. Haykin Cognitive Dynamic Systems, Hardback (March 2012)

A groundbreaking book from Simon Haykin, setting out the fundamental ideas and highlighting a range of future research directions.

Multiple-Input Multiple-Output Channel Models by Simon S. Haykin Multiple-Input Multiple-Output Channel Models, Hardback (April 2010)

Because Wideband Multiple Input and Multiple Output (MIMO) technology is just now being implemented in hardware, there is currently a great desire for knowledge of both the theory and practicality of its channels.

» View all books by Simon S. Haykin

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Author Biography - Simon S. Haykin

SIMON HAYKIN, PhD, is Professor of Electrical Engineering at the Communication Research Laboratory of McMaster University in Hamilton, Ontario, Canada.

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