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Complex Valued Amari_Hopfield Neural Network: Convergence Theorem

EasyChair Preprint 11550

4 pagesDate: December 17, 2023

Abstract

In  this   research  paper,  a  simplified  expression  for  the  energy  function  of  a  complex  Hopfield  neural  network  is  derived.  Based  on  that  expression,  a  simplified  proof  of   convergence  Theorem  is   proposed. Several  interesting  results  related  to  convergence  Theorem  are   proved.

Keyphrases: Hopfield neural network, convergence theorem, epsilon perturbation, quadratic form, stable states

BibTeX entry
BibTeX does not have the right entry for preprints. This is a hack for producing the correct reference:
@booklet{EasyChair:11550,
  author    = {Rama Garimella and Shaik Salma},
  title     = {Complex  Valued  Amari_Hopfield  Neural  Network:  Convergence  Theorem},
  howpublished = {EasyChair Preprint 11550},
  year      = {EasyChair, 2023}}
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