Relaxation of Coefficient Sensitiveness to Performance for Neural Networks Using Neuron Filter through Total Coloring Problems

Yoichi TAKENAKA  Nobuo FUNABIKI  Teruo HIGASHINO  

Publication
IEICE TRANSACTIONS on Fundamentals of Electronics, Communications and Computer Sciences   Vol.E84-A   No.9   pp.2367-2370
Publication Date: 2001/09/01
Online ISSN: 
DOI: 
Print ISSN: 0916-8508
Type of Manuscript: LETTER
Category: Neural Networks and Bioengineering
Keyword: 
Hopfield neural network,  parameter tuning,  neuron filter,  coefficient sensitiveness,  

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Summary: 
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.