Presentation | 1999/10/21 Estimation of a membership function using self-organizing neural network Hiroki Aoki, Toshimichi Saito, |
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PDF Download Page | PDF download Page Link |
Abstract(in Japanese) | (See Japanese page) |
Abstract(in English) | This paper proposes a novel algorithm for strengthen clustering functions in self-organizing maps. This algorithm can realize flexible clustering functions by adjusting connection strength between the winner neuron and the neighbor neuron. We then bring the problem to apply an automatic design of the membership function from experimental data. |
Keyword(in Japanese) | (See Japanese page) |
Keyword(in English) | Self-organizing feature map / Clustering / Fuzzy control / Membership function |
Paper # | NC99-39 |
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Committee | NC |
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Conference Date | 1999/10/21(1days) |
Place (in Japanese) | (See Japanese page) |
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Topics (in Japanese) | (See Japanese page) |
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Paper Information | |
Registration To | Neurocomputing (NC) |
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Language | JPN |
Title (in Japanese) | (See Japanese page) |
Sub Title (in Japanese) | (See Japanese page) |
Title (in English) | Estimation of a membership function using self-organizing neural network |
Sub Title (in English) | |
Keyword(1) | Self-organizing feature map |
Keyword(2) | Clustering |
Keyword(3) | Fuzzy control |
Keyword(4) | Membership function |
1st Author's Name | Hiroki Aoki |
1st Author's Affiliation | Department of Electronics and Electrical Engineering, HOSEI University() |
2nd Author's Name | Toshimichi Saito |
2nd Author's Affiliation | Department of Electronics and Electrical Engineering, HOSEI University |
Date | 1999/10/21 |
Paper # | NC99-39 |
Volume (vol) | vol.99 |
Number (no) | 382 |
Page | pp.pp.- |
#Pages | 6 |
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