Presentation 2011-01-24
Array-enhanced stochastic resonance in a network of locally-coupled excitable neuron circuits
Gessyca TOVAR, Tetsuya ASAI, Yoshihito AMEMIYA,
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Abstract(in English) Array-enhanced stochastic resonance (AESR), refers to the enhancing of the Stochastic Resonance (SR) phenomenon by couplings between neurons. Stacy et. al. showed that an array of simulated hippocampal CAl neurons exhibited SR-like behaviors where an optimal correlation between a sub-threshold input and the output could be obtained by tuning the noise intensity and coupling strength between the neurons. Based on these findings, we proposed a neural network model suitable for semiconductor devices. We designed an electrical neuromorphic network for the simple model and performed simulations using the wave propagation characteristic of the network as noise sources. We confirmed that the correlation value between the input and output increased as function of both, the noise and coupling strength.
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Keyword(in English) Array-enhanced stochastic resonance / oscillators / electrical circuits
Paper # NLP2010-132,NC2010-96
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Committee NC
Conference Date 2011/1/17(1days)
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Registration To Neurocomputing (NC)
Language ENG
Title (in Japanese) (See Japanese page)
Sub Title (in Japanese) (See Japanese page)
Title (in English) Array-enhanced stochastic resonance in a network of locally-coupled excitable neuron circuits
Sub Title (in English)
Keyword(1) Array-enhanced stochastic resonance
Keyword(2) oscillators
Keyword(3) electrical circuits
1st Author's Name Gessyca TOVAR
1st Author's Affiliation Graduate School of Information Science and Technology, Hokkaido University()
2nd Author's Name Tetsuya ASAI
2nd Author's Affiliation Graduate School of Information Science and Technology, Hokkaido University
3rd Author's Name Yoshihito AMEMIYA
3rd Author's Affiliation Graduate School of Information Science and Technology, Hokkaido University
Date 2011-01-24
Paper # NLP2010-132,NC2010-96
Volume (vol) vol.110
Number (no) 388
Page pp.pp.-
#Pages 6
Date of Issue