Presentation | 2003/11/14 Robotic Control by Volterra Netwerk Yoshikazu FUJISUE, Eiichi INOHIRA, Hirokazu YOKOI, |
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Abstract(in Japanese) | (See Japanese page) |
Abstract(in English) | In the conventional feedback error learning method, a hierarchical neural network by using a learning threshold element has been employed. However, a hierarchical neural network by using a learning threshold element cannot achieve the performance of processing a time series signal and controlling a system as much as we expected. The reason is that this neural network has low ability of processing a time series signal. We apply a hierarchical neural network by using volterra element, which has high ability of processing a time series signal. We embed the feed back error learning method into a control system of a robot, and verify the effectiveness of a volterra network by comparing the error in case of using the conventional hierarchical neural network. |
Keyword(in Japanese) | (See Japanese page) |
Keyword(in English) | Feedback error learning method / Volterra netwerk / Robot |
Paper # | NC2003-78 |
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Committee | NC |
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Conference Date | 2003/11/14(1days) |
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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) | Robotic Control by Volterra Netwerk |
Sub Title (in English) | |
Keyword(1) | Feedback error learning method |
Keyword(2) | Volterra netwerk |
Keyword(3) | Robot |
1st Author's Name | Yoshikazu FUJISUE |
1st Author's Affiliation | Kyusyu Institute of Technology Graduate School of Life Science and Systems Engineering() |
2nd Author's Name | Eiichi INOHIRA |
2nd Author's Affiliation | Kyusyu Institute of Technology Graduate School of Life Science and Systems Engineering |
3rd Author's Name | Hirokazu YOKOI |
3rd Author's Affiliation | Kyusyu Institute of Technology Graduate School of Life Science and Systems Engineering |
Date | 2003/11/14 |
Paper # | NC2003-78 |
Volume (vol) | vol.103 |
Number (no) | 465 |
Page | pp.pp.- |
#Pages | 5 |
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