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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Detalles Bibliográficos
Clasificación:Libro Electrónico
Autor principal: Ansari, Mohd. Samar (Autor)
Autor Corporativo: SpringerLink (Online service)
Formato: Electrónico eBook
Idioma:Inglés
Publicado: New Delhi : Springer India : Imprint: Springer, 2014.
Edición:1st ed. 2014.
Colección:Studies in Computational Intelligence, 508
Temas:
Computational intelligence.
Electronic circuits.
Neural networks (Computer science) .
Electronics.
Computational Intelligence.
Electronic Circuits and Systems.
Mathematical Models of Cognitive Processes and Neural Networks.
Electronics and Microelectronics, Instrumentation.
Acceso en línea:Texto Completo
Tabla de Contenidos:
  • 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.

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