Presentation | 2002/6/20 Learning for Periodic Function Using Neural Network with Characteristics of Inertia, Viscosity, and Stiffness Kunihiko NAKAZONO, Hiroshi KINJO, Tetsuhiko YAMAMOTO, |
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Abstract(in Japanese) | (See Japanese page) |
Abstract(in English) | This paper proposes a neural network with characteristics of inertia, viscosity, and stiffness and its learning algorithm based on back propagation method. The simulation results show that the neural network with characteristics of inertia, viscosity, and stiffness learned by the back propagation method has good performances of the training for time series patterns which generated from sine functions. |
Keyword(in Japanese) | (See Japanese page) |
Keyword(in English) | Neural network / Characteristic of inertia / Characteristic of viscosity / Characteristic of stiffness / Back propagation method / Recurrent neural network |
Paper # | NC2002-10 |
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Conference Information | |
Committee | NC |
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Conference Date | 2002/6/20(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 | 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 for Periodic Function Using Neural Network with Characteristics of Inertia, Viscosity, and Stiffness |
Sub Title (in English) | |
Keyword(1) | Neural network |
Keyword(2) | Characteristic of inertia |
Keyword(3) | Characteristic of viscosity |
Keyword(4) | Characteristic of stiffness |
Keyword(5) | Back propagation method |
Keyword(6) | Recurrent neural network |
1st Author's Name | Kunihiko NAKAZONO |
1st Author's Affiliation | Faculty of Engineering, University of the Ryukyus() |
2nd Author's Name | Hiroshi KINJO |
2nd Author's Affiliation | Faculty of Engineering, University of the Ryukyus |
3rd Author's Name | Tetsuhiko YAMAMOTO |
3rd Author's Affiliation | Faculty of Engineering, University of the Ryukyus |
Date | 2002/6/20 |
Paper # | NC2002-10 |
Volume (vol) | vol.102 |
Number (no) | 157 |
Page | pp.pp.- |
#Pages | 5 |
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