Development of NEural network simulator for structure-activity COrrelation of molecules:Neco. (3). Performance Evaluation of Self-organized Network and Perceptron.

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  • 分子の構造活性相関解析のためのニューラルネットワークシミュレータ：Ｎｅｃｏの開発　（３）　　組み合わせモデルとパーセプトロンの性能比較
  • ブンシ ノ コウゾウ カッセイ ソウカン カイセキ ノ タメ ノ ニューラル
  • Performance Evaluation of Self-organized Network and Perceptron
  • 組み合わせモデルとパーセプトロンの性能比較

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Abstract

A Self-organized network model for high-speed learning was included in the perceptron type Neural network simulator for structure-activity correlation of molecules : Neco. The performance of the Self-organized network model was compared with that of perceptron using twodimensional exclusive OR problem and the relationship between 13C-NMR shift and the conformation of norbornane. For practical use, the speed for convergence of the Self-organized network is almost four times faster than that of perceptron though perceptron gives higher order convergence. In the case of 13C-NMR shift and conformation of norbornane, a Self-organized network seems to show strong nonlinear classification in comparsion with perceptron.

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