A GA-Based Learning Algorithm for Binary Neural Networks(Regular Section)

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概要

• 論文の詳細を見る

• This paper presents a flexible learning algorithm for the binary neural network that can realize a desired Boolean function. The algorithm determines hidden layer parameters using a genetic algorithm. It can reduce the number of hidden neurons and can suppress parameters dispersion. These advantages are verified by basic numerical experiments

• 社団法人電子情報通信学会の論文
• 2002-11-01

著者

• Saito Toshimichi

  Department Of Electrical And Electronic Engineering Hosei University

• SAITO Toshimichi

  the Department of Electronics and Electrical Engineering, Hosei University

• Saito T

  The Department Of Electronics Electrical And Computer Engineering Hosei University

• SHIMADA Masanori

  the Department of Electronics, Electrical and Computer Engineering, Hosei University

• Shimada Masanori

  The Department Of Electronics Electrical And Computer Engineering Hosei University

• Saito Toshimichi

  The Department Of Electronics And Electrical Engineering Hosei University

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• A GA-Based Learning Algorithm for Binary Neural Networks(Regular Section)
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