Non-Linear Feedback Neural Networks VLSI Implementations and Applications
This book aims to present a viable alternative to the Hopfield Neural Network (HNN) model for analog computation. It is well known that the standard HNN suffers from problems of convergence to local minima, and requirement of a large number of neurons and synaptic weights. Therefore, improved soluti...
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| Format: | eBook |
| Language: | English |
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New Delhi
Springer India
2014, 2014
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| Edition: | 1st ed. 2014 |
| Series: | Studies in Computational Intelligence
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| Online Access: | |
| Collection: | Springer eBooks 2005- - Collection details see MPG.ReNa |
| Summary: | This book aims to present a viable alternative to the Hopfield Neural Network (HNN) model for analog computation. It is well known that the standard HNN suffers from problems of convergence to local minima, and requirement of a large number of neurons and synaptic weights. Therefore, improved solutions are needed. The non-linear synapse neural network (NoSyNN) is one such possibility and is discussed in detail in this book. This book also discusses the applications in computationally intensive tasks like graph coloring, ranking, and linear as well as quadratic programming. The material in the book is useful to students, researchers and academician working in the area of analog computation |
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| Physical Description: | XXII, 201 p. 79 illus online resource |
| ISBN: | 9788132215639 |