Digital Neural Networks

Paperback | March 11, 1993

byS.Y. Kung

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Covering the fundamental theory and practical implementation of various neural models, this text provides a coherent exploration and a well structured presentation of the three most important aspects of the neural networks: application, algorithm, and architecture. It offers working knowledge of the various neural models, the fundamental theoretical basis, the potential application domains, and the basic implementation issues. Electrical Engineers, Computer Engineers and Computer Scientists will find this text invaluable.

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From Our Editors

Intended for engineers and researchers interested in the applications of neural networks to signal and image processing, this book is theoretically based with emphasis on application and implementation. Coverage includes neural networks for representation, unsupervised networks for association/classification, neural networks for genera...

From the Publisher

Covering the fundamental theory and practical implementation of various neural models, this text provides a coherent exploration and a well structured presentation of the three most important aspects of the neural networks: application, algorithm, and architecture. It offers working knowledge of the various neural models, the ...

Format:PaperbackDimensions:400 pages, 9.5 × 7.25 × 0.88 inPublished:March 11, 1993Publisher:Pearson Education

The following ISBNs are associated with this title:

ISBN - 10:0136123260

ISBN - 13:9780136123262

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Table of Contents



 1. Overview.


 2. Neural Networks for Representation.


 3. Unsupervised Networks for Association/Classification.


 4. Supervised Networks for Classification.


 5. Neural Networks for Generalization/Restoration.


 6. Neural Net and Conventional Optimization Techniques.


 7. Special-Purpose Supercomputers for Neural Nets.

From Our Editors

Intended for engineers and researchers interested in the applications of neural networks to signal and image processing, this book is theoretically based with emphasis on application and implementation. Coverage includes neural networks for representation, unsupervised networks for association/classification, neural networks for generalization/restoration, neural net and conventional optimization techniques, and special purpose supercomputers for neural nets