| Presentation | 1998/5/25 Optimally Generalizing Neural Networks with Ability of Recovering from Single Stuck-at Zero Faults Hidekazu IWAKI, Hidemitsu OGAWA, |
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| PDF Download Page | PDF download Page Link |
| Abstract(in Japanese) | (See Japanese page) |
| Abstract(in English) | During design of hardware for multilayer neural networks, it is necessary to take measures against operational faults. In this paper, We propose a method to recover functionality of multilayer neural networks after single stuck-at zero faults using only a modification of weights. First, the necessary and sufficient conditions are derived for the number of hidden units and basis functions to realize the method. Then, based on these conditions we construct basis functions and algorithms to modify weights. |
| Keyword(in Japanese) | (See Japanese page) |
| Keyword(in English) | feed forward neural network / stuck-at fault / fault tolerance |
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| Committee | NC |
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| Conference Date | 1998/5/25(1days) |
| Place (in Japanese) | (See Japanese page) |
| Place (in English) | |
| Topics (in Japanese) | (See Japanese page) |
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| 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) | Optimally Generalizing Neural Networks with Ability of Recovering from Single Stuck-at Zero Faults |
| Sub Title (in English) | |
| Keyword(1) | feed forward neural network |
| Keyword(2) | stuck-at fault |
| Keyword(3) | fault tolerance |
| 1st Author's Name | Hidekazu IWAKI |
| 1st Author's Affiliation | Department of Computational Intelligence and Systems Science Interdisciplinary Graduate School of Science and Engineering, Tokyo Institute of Technology() |
| 2nd Author's Name | Hidemitsu OGAWA |
| 2nd Author's Affiliation | Department of Computer Science, Graduate School of Information Science and Engineering Tokyo Institute of Technology |
| Date | 1998/5/25 |
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| Volume (vol) | vol.98 |
| Number (no) | 77 |
| Page | pp.pp.- |
| #Pages | 8 |
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