| Presentation | 2007/3/9 Fuzzy Neural Network with Inhibition Layer Junji YAMAMOTO, Satoshi MATSUDA, |
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| PDF Download Page | PDF download Page Link |
| Abstract(in Japanese) | (See Japanese page) |
| Abstract(in English) | The proposed FNN has two phases. 1) Initial Learning phase 2) Additional Learning phase. In the Initial Learning phase, using input-output space considered clustering, we attempted improvement of recognition ability of FNN. In the Additional Learning phase, implementing a inhibition layer, we attempted improvement of additional learning on FNN. In the simulation of Letter Recognition, the proposed FNN obtained excellent results in both Initial Learning and Additional Learning. |
| Keyword(in Japanese) | (See Japanese page) |
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| Paper # | AI2006-57 |
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| Conference Information | |
| Committee | AI |
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| Conference Date | 2007/3/9(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 | Artificial Intelligence and Knowledge-Based Processing (AI) |
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| Language | JPN |
| Title (in Japanese) | (See Japanese page) |
| Sub Title (in Japanese) | (See Japanese page) |
| Title (in English) | Fuzzy Neural Network with Inhibition Layer |
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| 1st Author's Name | Junji YAMAMOTO |
| 1st Author's Affiliation | Graduate Department of Mathematical Information Engineering, Postgraduate of Industrial Technology Nihon University() |
| 2nd Author's Name | Satoshi MATSUDA |
| 2nd Author's Affiliation | Department of Mathematical Information Engineering, College of Industrial Technology Nihon University |
| Date | 2007/3/9 |
| Paper # | AI2006-57 |
| Volume (vol) | vol.106 |
| Number (no) | 587 |
| Page | pp.pp.- |
| #Pages | 8 |
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