| Presentation | 1996/5/24 Learning Dynamical Systems Produced by Recurrent Neural Networks Masahiro KIMURA, Ryohei NAKANO, |
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| PDF Download Page | PDF download Page Link |
| Abstract(in Japanese) | (See Japanese page) |
| Abstract(in English) | In this paper, the concept of a neural dynamical system is proposed to investigate mathematically the learning of a dynamical system by a recurrent neural network with hidden units. We present the conditions for our recurrent neural network to produce a neural dynamical system, and also discuss the possibility of identifying a neural dynamical system via the learning of its temporal trajectories. |
| Keyword(in Japanese) | (See Japanese page) |
| Keyword(in English) | recurrent neural network / dynamical system / learning / hidden units / temporal trajectory |
| Paper # | NC96-6 |
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| Conference Information | |
| Committee | NC |
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| Conference Date | 1996/5/24(1days) |
| Place (in Japanese) | (See Japanese page) |
| Place (in English) | |
| 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) | Learning Dynamical Systems Produced by Recurrent Neural Networks |
| Sub Title (in English) | |
| Keyword(1) | recurrent neural network |
| Keyword(2) | dynamical system |
| Keyword(3) | learning |
| Keyword(4) | hidden units |
| Keyword(5) | temporal trajectory |
| 1st Author's Name | Masahiro KIMURA |
| 1st Author's Affiliation | NTT Communication Science Laboratories() |
| 2nd Author's Name | Ryohei NAKANO |
| 2nd Author's Affiliation | NTT Communication Science Laboratories |
| Date | 1996/5/24 |
| Paper # | NC96-6 |
| Volume (vol) | vol.96 |
| Number (no) | 76 |
| Page | pp.pp.- |
| #Pages | 8 |
| Date of Issue | |