Non-Linear Feedback Neural Networks

VLSI Implementations and Applications

  • Mohd. SamarĀ Ansari

Part of the Studies in Computational Intelligence book series (SCI, volume 508)

Table of contents

  1. Front Matter
    Pages i-xxii
  2. Mohd. Samar Ansari
    Pages 1-11
  3. Mohd. Samar Ansari
    Pages 13-54
  4. Mohd. Samar Ansari
    Pages 187-190
  5. Back Matter
    Pages 191-201

About this book

Introduction

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.

Keywords

Graph Coloring Hardware Simulation Hopfield Neural Network Mathematical Programming Neural Networks Non-Linear Feedback Transcendental Energy Function

Authors and affiliations

  • Mohd. SamarĀ Ansari
    • 1
  1. 1.Electronics EngineeringAligrah Muslim UniversityAligarhIndia

Bibliographic information

  • DOI https://doi.org/10.1007/978-81-322-1563-9
  • Copyright Information Springer India 2014
  • Publisher Name Springer, New Delhi
  • eBook Packages Engineering
  • Print ISBN 978-81-322-1562-2
  • Online ISBN 978-81-322-1563-9
  • Series Print ISSN 1860-949X
  • Series Online ISSN 1860-9503
  • About this book