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Non-Linear Feedback Neural Networks

VLSI Implementations and Applications

Medium: Buch
ISBN: 978-81-322-2896-7
Verlag: Springer India
Erscheinungstermin: 27.08.2016
Lieferfrist: bis zu 10 Tage

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.


Produkteigenschaften


  • Artikelnummer: 9788132228967
  • Medium: Buch
  • ISBN: 978-81-322-2896-7
  • Verlag: Springer India
  • Erscheinungstermin: 27.08.2016
  • Sprache(n): Englisch
  • Auflage: Softcover Nachdruck of the original 1. Auflage 2014
  • Serie: Studies in Computational Intelligence
  • Produktform: Kartoniert, Previously published in hardcover
  • Gewicht: 347 g
  • Seiten: 201
  • Format (B x H x T): 155 x 235 x 13 mm
  • Ausgabetyp: Kein, Unbekannt
Autoren/Hrsg.

Autoren

Introduction.- Background.- Voltage-mode Neural Network for the Solution of Linear Equations.- Mixed-mode Neural Circuit for Solving Linear Equations.- Non-Linear Feedback Neural Circuits for Linear and Quadratic Programming.- OTA-based Implementations of Mixed-mode Neural Circuits.- Appendix A: Mixed-mode Neural Network for Graph Colouring.- Appendix B: Mixed-mode Neural Network for Ranking.