Presentation | 2002/1/21 Negative Resistance Influence on Neural Networks Koji NAKAJIMA, Yoshihiro HAYAKAWA, |
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Abstract(in English) | Many models of neural cells and networks have been proposed and investigated. It is an important characteristic to have an ability of excitation for neurons. A normal neuron, which, however, seldom shows spontaneous excitations, is ordinarily in a resting state. And it fires depending on inputs from other neurons and external stimulations. It seems to be a good condition for the neurons which are in the critical state to be able to fire. The condition is also considered to have many rolls for the functions of neural networks. It is an elementary assumption to have two states resting and excitation for neurons in the past network models. And hence, it seems few discussins have been presented what rolls the neuro in the critical state has on the network actions. In this paper, we present the novel model (Inverse Delayed Mode1) to represent neurons in the critical state, and discuss the fundamental characteristics of the ID model. |
Keyword(in Japanese) | (See Japanese page) |
Keyword(in English) | Neural Networks / Negative Resistance / BVP model / Hysteresis Neuron |
Paper # | NLP2001-90(2002-01) |
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Committee | NLP |
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Conference Date | 2002/1/21(1days) |
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Registration To | Nonlinear Problems (NLP) |
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Language | JPN |
Title (in Japanese) | (See Japanese page) |
Sub Title (in Japanese) | (See Japanese page) |
Title (in English) | Negative Resistance Influence on Neural Networks |
Sub Title (in English) | |
Keyword(1) | Neural Networks |
Keyword(2) | Negative Resistance |
Keyword(3) | BVP model |
Keyword(4) | Hysteresis Neuron |
1st Author's Name | Koji NAKAJIMA |
1st Author's Affiliation | Laboratory for Electronic Intelligent Systems Research Institute of Electrical Communication, Tohoku University() |
2nd Author's Name | Yoshihiro HAYAKAWA |
2nd Author's Affiliation | Laboratory for Electronic Intelligent Systems Research Institute of Electrical Communication, Tohoku University |
Date | 2002/1/21 |
Paper # | NLP2001-90(2002-01) |
Volume (vol) | vol.101 |
Number (no) | 613 |
Page | pp.pp.- |
#Pages | 8 |
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