Presentation | 1995/5/19 Basins of the Optimal States in Learning Dynamical Systems Hiroyuki Nakajima, Yoshisuke Ueda, |
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Abstract(in Japanese) | (See Japanese page) |
Abstract(in English) | A new phenomenon called a "riddled basin", which is an extremely complicated domain of attraction usually accompanying invariant sets for dynamical systems driven by chaotic signal, e.g. chaotic synchronizing systems, have been drawing attention of nonlinear scientists. In this report, the optimal state of a back-propagation learning of chaotic time series is shown to be a "locally riddled basin" by a numerical experiment. It is also proved that the optimal state of learning the parameter of the tent map by a gradient-descent method can be an attractor with a riddled basin. |
Keyword(in Japanese) | (See Japanese page) |
Keyword(in English) | basin / neural network / back-propagation / dynamical system / chaos / gradient-descent method |
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Committee | NLP |
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Conference Date | 1995/5/19(1days) |
Place (in Japanese) | (See Japanese page) |
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Topics (in Japanese) | (See Japanese page) |
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Registration To | Nonlinear Problems (NLP) |
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Language | ENG |
Title (in Japanese) | (See Japanese page) |
Sub Title (in Japanese) | (See Japanese page) |
Title (in English) | Basins of the Optimal States in Learning Dynamical Systems |
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Keyword(1) | basin |
Keyword(2) | neural network |
Keyword(3) | back-propagation |
Keyword(4) | dynamical system |
Keyword(5) | chaos |
Keyword(6) | gradient-descent method |
1st Author's Name | Hiroyuki Nakajima |
1st Author's Affiliation | Department of Electrical and Electronic Engineering Faculty of Engineering, Kyoto University() |
2nd Author's Name | Yoshisuke Ueda |
2nd Author's Affiliation | Department of Electrical and Electronic Engineering Faculty of Engineering, Kyoto University |
Date | 1995/5/19 |
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Volume (vol) | vol.95 |
Number (no) | 47 |
Page | pp.pp.- |
#Pages | 8 |
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