Inverse Function Delayed Model for Optimization Problems

Yoshihiro Hayakawa, Tatsuaki Denda, Koji Nakajima

Research output: Contribution to journalArticlepeer-review

6 Citations (Scopus)

Abstract

The ID model is a novel model derived from a macroscopic model that is attached to conventional network action, and the important character is what we can introduce negative resistance effect into. In this paper, we aim at the unstabilization of local minimum states, which is a big problem to solving optimization problems in a neural network, by the action of this negative resistance effect, and we show the good performance by numerical experiments.

Original languageEnglish
Pages (from-to)981-987
Number of pages7
JournalLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume3213
Publication statusPublished - 2004 Dec 1

ASJC Scopus subject areas

  • Theoretical Computer Science
  • Computer Science(all)

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