Neural Networks : Advances and Applications II

by
Format: Hardcover
Pub. Date: 1992-07-01
Publisher(s): Elsevier Science Ltd
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Summary

The present volume is a natural follow-up to Neural Networks: Advances and Applications which appeared one year previously. As the title indicates, it combines the presentation of recent methodological results concerning computational models and results inspired by neural networks, and of well-documented applications which illustrate the use of such models in the solution of difficult problems. The volume is balanced with respect to these two orientations: it contains six papers concerning methodological developments and five papers concerning applications and examples illustrating the theoretical developments. Each paper is largely self-contained and includes a complete bibliography.The methodological part of the book contains two papers on learning, one paper which presents a computational model of intracortical inhibitory effects, a paper presenting a new development of the random neural network, and two papers on associative memory models. The applications and examples portion contains papers on image compression, associative recall of simple typed images, learning applied to typed images, stereo disparity detection, and combinatorial optimisation.

Table of Contents

Preface
Learning in the Recurrent Random Neural Networkp. 1
Generalization Performance of Feed-Forward Neural Networksp. 13
The Nature of Intracortical Inhibitory Effectsp. 39
Random Neural Networks with Multiple Classes of Signalsp. 83
The MicroCircuit Associative Memory, uAM: A Biologically Motivated Memory Architecturep. 95
Generalised Associative Memory and the Computation of Membership Functionsp. 129
Layered Neural Network for Stereo Disparity Detectionp. 141
Storage and Recognition Methods for the Random Neural Networkp. 155
Neural Networks for Image Compressionp. 177
Autoassociative Memory with the Random Neural Network using Gelenbe's Learning Algorithmp. 199
Minimum Graph Covering with the Random Neural Network Modelp. 215
Table of Contents provided by Blackwell. All Rights Reserved.

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