Equivalence between some dynamical systems for optimization

Kiichi Urahama

Research output: Contribution to journalArticle

Abstract

It is shown by the derivation of solution methods for an elementary optimization problem that the stochastic relaxation in image analysis, the Potts neural networks for combinatorial optimization and interior point methods for nonlinear programming have common formulation of their dynamics. This unification of these algorithms leads us to possibility for real time solution of these problems with common analog electronic circuits.

Original languageEnglish
Pages (from-to)268-271
Number of pages4
JournalIEICE Transactions on Fundamentals of Electronics, Communications and Computer Sciences
VolumeE78-A
Issue number2
Publication statusPublished - Feb 1995
Externally publishedYes

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Analogue Electronic Circuits
Interior Point Method
Combinatorial optimization
Combinatorial Optimization
Nonlinear programming
Unification
Nonlinear Programming
Image Analysis
Image analysis
Dynamical systems
Dynamical system
Equivalence
Neural Networks
Optimization Problem
Neural networks
Optimization
Formulation
Networks (circuits)

All Science Journal Classification (ASJC) codes

  • Hardware and Architecture
  • Information Systems
  • Electrical and Electronic Engineering

Cite this

Equivalence between some dynamical systems for optimization. / Urahama, Kiichi.

In: IEICE Transactions on Fundamentals of Electronics, Communications and Computer Sciences, Vol. E78-A, No. 2, 02.1995, p. 268-271.

Research output: Contribution to journalArticle

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