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
Autor principal: Ansari, Mohd. Samar
Formato: Libro electrónico
Lenguaje:Inglés
Publicado: New Delhi : Springer India : Imprint: Springer, 2014.
Colección:Studies in Computational Intelligence, 508
Materias:
Neural networks (Computer science).
Electronics.
Microelectronics.
Electronic circuits.
Engineering.
Computational Intelligence.
Circuits and Systems.
Mathematical Models of Cognitive Processes and Neural Networks.
Instrumentation.
Acceso en línea:http://dx.doi.org/10.1007/978-81-322-1563-9
Aporte de:Registro referencial: Solicitar el recurso aquí
Bibliotecas (ING-UNLP) de Universidad Nacional de La Plata
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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