Presentation 1999/2/8
Reconstruction of Time Series via a Network of Stochastic Resonance Neurons
Tomokazu Yanai, Isao Tokuda, Tomomasa Nagashima, Kazuyuki Aihara,
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Abstract(in English) As a new understanding of biological sensory mechanism for input signal detection, stochastic resonance phenomenon has been recently paid a great deal of attention. In particular, Collins et al. reports that a large network or stochastic resonance elements gives rise to a robust sensory mechanism for detecting a variety or complex input signals. In this study, we investigate the effectiveness of such stochastic resonance network to chaotic input signals.
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Keyword(in English) Stochastic Resonance / Summing Network / Reconstruction / of Time Series / Chaos
Paper # NLP98-96
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Conference Information
Committee NLP
Conference Date 1999/2/8(1days)
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Paper Information
Registration To Nonlinear Problems (NLP)
Language JPN
Title (in Japanese) (See Japanese page)
Sub Title (in Japanese) (See Japanese page)
Title (in English) Reconstruction of Time Series via a Network of Stochastic Resonance Neurons
Sub Title (in English)
Keyword(1) Stochastic Resonance
Keyword(2) Summing Network
Keyword(3) Reconstruction
Keyword(4) of Time Series
Keyword(5) Chaos
1st Author's Name Tomokazu Yanai
1st Author's Affiliation Department of Computer Science and Systems Engineering, Murolan Institute of Technology()
2nd Author's Name Isao Tokuda
2nd Author's Affiliation Department of Computer Science and Systems Engineering, Murolan Institute of Technology
3rd Author's Name Tomomasa Nagashima
3rd Author's Affiliation Department of Computer Science and Systems Engineering, Murolan Institute of Technology
4th Author's Name Kazuyuki Aihara
4th Author's Affiliation Department of Mathematical Engineering and Information Physics, Faculty of Engineering, The University
Date 1999/2/8
Paper # NLP98-96
Volume (vol) vol.98
Number (no) 582
Page pp.pp.-
#Pages 5
Date of Issue