Non-Linear Feedback Neural Networks

VLSI Implementations and Applications

Nonfiction, Science & Nature, Technology, Electronics, Circuits, Computers, Advanced Computing, Artificial Intelligence, General Computing
Cover of the book Non-Linear Feedback Neural Networks by Mohd. Samar Ansari, Springer India
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Author: Mohd. Samar Ansari ISBN: 9788132215639
Publisher: Springer India Publication: September 3, 2013
Imprint: Springer Language: English
Author: Mohd. Samar Ansari
ISBN: 9788132215639
Publisher: Springer India
Publication: September 3, 2013
Imprint: Springer
Language: English

This book aims to present a viable alternative to the Hopfield Neural Network (HNN) model for analog computation. It is well known 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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This book aims to present a viable alternative to the Hopfield Neural Network (HNN) model for analog computation. It is well known 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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