| Presentation | 2009-11-11 Chaotic Time Series Prediction by Combining Echo-State Networks and Radial Basis Function Networks Yoshitaka ITOH, Masaharu ADACHI, |
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| PDF Download Page |  PDF download Page Link |
| Abstract(in Japanese) | (See Japanese page) |
| Abstract(in English) | In this report, we describe a chaotic time series prediction method by a network which combines echo state networks (ESN) with radial basis function networks (RBFN). ESN is a neural network consisting of three layers. The hidden layer is called a "reservoir" and consists of many neurons. RBFN is a neural network using radial basis function (RBF) for output function of the neurons. It represents non-linear functions by superimposing RBF functions. In numerical experiments, time series of the Mackey-Glass equation and the Langford equation are predicted. As a result, we find that the proposed model shows higher prediction ability than the conventional ESN. |
| Keyword(in Japanese) | (See Japanese page) |
| Keyword(in English) | Echo-State Network / Radial Basis Function Network / chaotic time series |
| Paper # | NLP2009-86 |
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| Conference Information | |
| Committee | NLP |
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| Conference Date | 2009/11/4(1days) |
| Place (in Japanese) | (See Japanese page) |
| Place (in English) | |
| 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) | Chaotic Time Series Prediction by Combining Echo-State Networks and Radial Basis Function Networks |
| Sub Title (in English) | |
| Keyword(1) | Echo-State Network |
| Keyword(2) | Radial Basis Function Network |
| Keyword(3) | chaotic time series |
| 1st Author's Name | Yoshitaka ITOH |
| 1st Author's Affiliation | Department of Electronic Engineering, Graduate School of Engineering, Tokyo Denki University() |
| 2nd Author's Name | Masaharu ADACHI |
| 2nd Author's Affiliation | Department of Electronic Engineering, Graduate School of Engineering, Tokyo Denki University |
| Date | 2009-11-11 |
| Paper # | NLP2009-86 |
| Volume (vol) | vol.109 |
| Number (no) | 269 |
| Page | pp.pp.- |
| #Pages | 4 |
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