Presentation | 1994/5/20 On Patten presentation for learning One-demensional discrete dynamical systems in neural networks Hiroyuki Nakajima, Takafumi / Ohnishi, |
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Abstract(in Japanese) | (See Japanese page) |
Abstract(in English) | How the restriction on the size of training set and modification of distribution density and time correlation affect thd speed and accuracy of learning discrete dynamical systems in neural networks are studied by numerical experiments on learning Cubic map and Logistic map.These systems can be learned with about 20 training data as accurately as learning with infinite data.Acceleration of learning by trajectory error method is also observed.The distribution density of patterns plays a more important role in learning than time correlation. |
Keyword(in Japanese) | (See Japanese page) |
Keyword(in English) | neural network / back propagation / discrete dynamical system / chaos / invariant measure |
Paper # | NLP94-13 |
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Conference Information | |
Committee | NLP |
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Conference Date | 1994/5/20(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 | 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) | On Patten presentation for learning One-demensional discrete dynamical systems in neural networks |
Sub Title (in English) | |
Keyword(1) | neural network |
Keyword(2) | back propagation |
Keyword(3) | discrete dynamical system |
Keyword(4) | chaos |
Keyword(5) | invariant measure |
1st Author's Name | Hiroyuki Nakajima |
1st Author's Affiliation | Department of Electrical Engineering II,Faculty of Engineering Kyoto University() |
2nd Author's Name | Takafumi / Ohnishi |
2nd Author's Affiliation | Department of Electrical Engineering II,Faculty of Engineering Kyoto University |
Date | 1994/5/20 |
Paper # | NLP94-13 |
Volume (vol) | vol.94 |
Number (no) | 45 |
Page | pp.pp.- |
#Pages | 8 |
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