diffuse algorithms for neural and neuro

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Diffuse Algorithms for Neural and Neuro Fuzzy Networks
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Publisher : Butterworth-Heinemann
Release Date :
ISBN 10 : 0128126108
Pages : 220 pages
Rating : /5 ( users)
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Diffuse Algorithms for Neural and Neuro-Fuzzy Networks: With Applications in Control Engineering and Signal Processing presents new approaches to training neural and neuro-fuzzy networks. This book is divided into six chapters. Chapter 1 consists of plants models reviews, problems statements, and known results that are relevant to the subject matter of this book. Chapter 2 considers the RLS behavior on a finite interval. The theoretical results are illustrated by examples of solving problems of identification, control, and signal processing. Properties of the bias, the matrix of second-order moments and the normalized average squared error of the RLS algorithm on a finite time interval are studied in Chapter 3. Chapter 4 deals with the problem of multilayer neural and neuro-fuzzy networks training with simultaneous estimation of the hidden and output layers parameters. The theoretical results are illustrated with the examples of pattern recognition, identification of nonlinear static, and dynamic plants. Chapter 5 considers the estimation problem of the state and the parameters of the discrete dynamic plants in the absence of a priori statistical information about initial conditions or its incompletion. The Kalman filter and the extended Kalman filter diffuse analogues are obtained. Finally, Chapter 6 provides examples of the use of diffuse algorithms for solving problems in various engineering applications. This book is ideal for researchers and graduate students in control, signal processing, and machine learning. Presents a new approach to training which can be applied to solve the control, identification, signal processing, and classification problems arising in practice Offers an improvement from the existing learning techniques in control, robotics, and machine learning Provides examples of the use of diffuse algorithms for solving problems in various engineering applications

Diffuse Algorithms for Neural and Neuro Fuzzy Networks

Diffuse Algorithms for Neural and Neuro-Fuzzy Networks: With Applications in Control Engineering and Signal Processing presents new approaches to training neural and neuro-fuzzy networks. This book is divided into six chapters. Chapter 1 consists of plants models reviews, problems statements, and known results that are relevant to the subject matter of

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Diffuse Algorithms for Neural Networks

The problem of neural and neuro-fuzzy networks training is considered in this book. The author's attention is concentrated on the approaches which are based on the use of a separable structure of plants models--nonlinear with respect to some unknown parameters and linear relating to the others. It may be, for

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This book provides comprehensive introduction to a consortium of technologies underlying soft computing, an evolving branch of computational intelligence. The constituent technologies discussed comprise neural networks, fuzzy logic, genetic algorithms, and a number of hybrid systems which include classes such as neuro-fuzzy, fuzzy-genetic, and neuro-genetic systems. The hybridization of the

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The 1997 IEEE International Conference on Neural Networks  June 9 12  1997  Westin Galleria Hotel  Houston  Texas  USA

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Traumatic brain injury (TBI) remains a significant source of death and permanent disability, contributing to nearly one-third of all injury related deaths in the United States and exacting a profound personal and economic toll. Despite the increased resources that have recently been brought to bear to improve our understanding of

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Choice Outstanding Academic Title, 1996. In hundreds of articles by experts from around the world, and in overviews and "road maps" prepared by the editor, The Handbook of Brain Theory and Neural Networks charts the immense progress made in recent years in many specific areas related to great questions: How does

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