Presentation 2013-11-22
Statistical Mechanics of Neural Network Model with Sparse and Local Excitation
Akira MANDA, Jun KITAZONO, Toshiaki OMORI, Masato OKADA,
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Abstract(in English) In the present study, we propose a neural network model that generates the sparse and local excitation. Our model is based on two types of models. One is the neural network model that has Mexican-hat type interaction, and the other is the associative memory model. Our model generates the local excitation as is the case with the Mexican-hat-type network model, and can store a number of memory patterns on the local excitation as is the case with the associative memory model. The property of the system varies according to the firing rate of memory pattern in the associative memory model. We analyze the nature of our model for the case of various firing rates of the memory patterns. The analytical result shows that the sparse and local excitation in the proposed model can store a number of memory patterns only if the firing rate of the local excitation is equal to or lower than 50%.
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Keyword(in English) Mexican-hat type interaction / Associative memory model / Localized activity / Statistical mechanics / Sparseness
Paper # NC2013-46
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Committee NC
Conference Date 2013/11/15(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) Statistical Mechanics of Neural Network Model with Sparse and Local Excitation
Sub Title (in English)
Keyword(1) Mexican-hat type interaction
Keyword(2) Associative memory model
Keyword(3) Localized activity
Keyword(4) Statistical mechanics
Keyword(5) Sparseness
1st Author's Name Akira MANDA
1st Author's Affiliation Graduate School of Frontier Sciences, The University of Tokyo()
2nd Author's Name Jun KITAZONO
2nd Author's Affiliation Graduate School of Frontier Sciences, The University of Tokyo
3rd Author's Name Toshiaki OMORI
3rd Author's Affiliation Graduate School of Engineering, Kobe University
4th Author's Name Masato OKADA
4th Author's Affiliation Graduate School of Frontier Sciences, The University of Tokyo:RIKEN Brain Science Institute
Date 2013-11-22
Paper # NC2013-46
Volume (vol) vol.113
Number (no) 315
Page pp.pp.-
#Pages 6
Date of Issue