Presentation 2008-06-27
A Learning Algorithm of Binary Neural Networks Based on Real-Coded GA
Yu AKEDO, Hidehiro NAKANO, Arata MIYAUCHI,
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Abstract(in English) In this paper, we propose a learning algorithm of Binary Neural Networks (BNNs) based on real-coded genetic algorithm. The algorithm encodes parameters of hidden layer neurons as individuals consisting of real number vectors. The proposed algorithm can reduce the number of hidden layer neurons and has high generalization ability, comparing with the conventional algorithm. Through basic numerical experiments, we verify the advantages of the proposed method.
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Keyword(in English) 3 layer BNNs / GA-based learning / Real-coded GA / Generalization Ability / Supervised learning
Paper # NC2008-26
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Committee NC
Conference Date 2008/6/19(1days)
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Registration To Neurocomputing (NC)
Language JPN
Title (in Japanese) (See Japanese page)
Sub Title (in Japanese) (See Japanese page)
Title (in English) A Learning Algorithm of Binary Neural Networks Based on Real-Coded GA
Sub Title (in English)
Keyword(1) 3 layer BNNs
Keyword(2) GA-based learning
Keyword(3) Real-coded GA
Keyword(4) Generalization Ability
Keyword(5) Supervised learning
1st Author's Name Yu AKEDO
1st Author's Affiliation Musashi Institute of Technology()
2nd Author's Name Hidehiro NAKANO
2nd Author's Affiliation Musashi Institute of Technology
3rd Author's Name Arata MIYAUCHI
3rd Author's Affiliation Musashi Institute of Technology
Date 2008-06-27
Paper # NC2008-26
Volume (vol) vol.108
Number (no) 101
Page pp.pp.-
#Pages 4
Date of Issue