Presentation 2004/11/19
Representing the bifurcation structure of BVP neuron model onto a self-organising map by using modular network SOM (mnSOM)
Syuji KANEKO, Syozo YASUI, Tetsuo FURUKAWA,
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Abstract(in English) The modular network SOM (mnSOM) is a generalization of Kohonen's Self-Organizing Maps (SOM) in which each nodal unit is replaced by a function module instead of a weight vector. By employing a recurrent neural network (RNN) as the function module, the mnSOM acquires an ability to deal with dynamical systems. The RNN-module-mnSOM learns the dynamics from a set of time series data in parallel with generating a feature map which describes the underlying models as well as their relationships. In this paper, an application result of mnSOM to classifying task of neuronal firing patterns is reported.
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Keyword(in English) modular network / Self-Organizing Map / mnSOM / dynamical system / BVP neuron model
Paper # NLP2004-72,NC2004-88
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Committee NLP
Conference Date 2004/11/19(1days)
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Registration To Nonlinear Problems (NLP)
Language JPN
Title (in Japanese) (See Japanese page)
Sub Title (in Japanese) (See Japanese page)
Title (in English) Representing the bifurcation structure of BVP neuron model onto a self-organising map by using modular network SOM (mnSOM)
Sub Title (in English)
Keyword(1) modular network
Keyword(2) Self-Organizing Map
Keyword(3) mnSOM
Keyword(4) dynamical system
Keyword(5) BVP neuron model
1st Author's Name Syuji KANEKO
1st Author's Affiliation Department of Brain Science and Engineering, Kyushu Institute of Technology()
2nd Author's Name Syozo YASUI
2nd Author's Affiliation Department of Brain Science and Engineering, Kyushu Institute of Technology
3rd Author's Name Tetsuo FURUKAWA
3rd Author's Affiliation Department of Brain Science and Engineering, Kyushu Institute of Technology
Date 2004/11/19
Paper # NLP2004-72,NC2004-88
Volume (vol) vol.104
Number (no) 471
Page pp.pp.-
#Pages 6
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