Presentation 2005/3/21
A Frequency-Multiplexed Function-Approximation Coherent Lightwave Neural Network To Learn Optical Phase Values by Use of Volume Hologram
Amornrat LIMMANEE, Sotaro KAWATA, Akira HIROSE,
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Abstract(in English) We propose a frequency-multiplexed function-approximation coherent lightwave neural network to learn optical phase values by use of volume hologram. Frequency multiplexed learning is realized by the complex-valued Hebbian rule with changing optical carrier frequency task-dependently to obtain a frequency-dependent network behavior. Though the Hebbian learning has conventionally been used to construct an associative memory, we apply it to realize a function-approximation network. The basic idea is also presented. Optical experiment demonstrates that desired phase values are obtained as the output of the coherent neural network system.
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Keyword(in English) Coherent information processing / Volume hologram / Frequency-multiplexing / Complex-valued Hebbian learning rule / Function approximation
Paper # NC2004-155
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Committee NC
Conference Date 2005/3/21(1days)
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Language JPN
Title (in Japanese) (See Japanese page)
Sub Title (in Japanese) (See Japanese page)
Title (in English) A Frequency-Multiplexed Function-Approximation Coherent Lightwave Neural Network To Learn Optical Phase Values by Use of Volume Hologram
Sub Title (in English)
Keyword(1) Coherent information processing
Keyword(2) Volume hologram
Keyword(3) Frequency-multiplexing
Keyword(4) Complex-valued Hebbian learning rule
Keyword(5) Function approximation
1st Author's Name Amornrat LIMMANEE
1st Author's Affiliation Dept. of Frontier Informatics, The University of Tokyo()
2nd Author's Name Sotaro KAWATA
2nd Author's Affiliation Dept. of Frontier Informatics, The University of Tokyo
3rd Author's Name Akira HIROSE
3rd Author's Affiliation Dept. of Frontier Informatics, The University of Tokyo
Date 2005/3/21
Paper # NC2004-155
Volume (vol) vol.104
Number (no) 758
Page pp.pp.-
#Pages 6
Date of Issue