Relaxation of coefficient sensitiveness to performance for neural networks using neuron filter through total coloring problems

Y. Takenaka, Nobuo Funabiki, T. Higashino

Research output: Contribution to journalArticle


In this paper we show that the neuron filter is effective for relaxing the coefficient sensitiveness of the Hopfield neural network for combinatorial optimization problems. Since the parameters in motion equation have a significant influence on the performance of the neural network, many studies have been carried out to support determining the value of the parameters. However, not a few researchers have determined the value of the parameters experimentally yet. We show that the use of the neuron filter is effective for the parameter tuning, particularly for determining their values experimentally through simulations.

Original languageEnglish
Pages (from-to)2367-2370
Number of pages4
JournalIEICE Transactions on Fundamentals of Electronics, Communications and Computer Sciences
Issue number9
Publication statusPublished - Sep 2001
Externally publishedYes



  • Coefficient sensitiveness
  • Hopfield neural network
  • Neuron filter
  • Parameter tuning

ASJC Scopus subject areas

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

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