Fully-connected neural network model of associative memory as a test function of evolutionary computations

Akira Imada, Keijiro Araki

Research output: Contribution to journalArticlepeer-review

Abstract

We apply some variants of evolutionary computations to the fully-connected neural network model of associative memory. Among others when we regard it as a parameter optimization problem we notice that the model has some favorable properties as a test function of evolutionary computations. So far many functions have been proposed for comparative study. However as Whitley and his colleagues suggested many of the existing common test functions have some problems in comparing and evaluating evolutionary computations. In this paper we focus on the possibilities of using the fully-connected neural network model as a test function of evolutionary computations.

Original languageEnglish
Pages (from-to)318-325
Number of pages8
JournalIEICE Transactions on Information and Systems
VolumeE82-D
Issue number1
Publication statusPublished - 1999

All Science Journal Classification (ASJC) codes

  • Software
  • Hardware and Architecture
  • Computer Vision and Pattern Recognition
  • Electrical and Electronic Engineering
  • Artificial Intelligence

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