Presentation | 1997/5/23 Geometric Learning Algorithm for Elementary Perceptron : Convergence Condition and Noise Performance Seiji MIYOSHI, Kenji NAKAYAMA, Kazushi IKEDA, |
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Abstract(in Japanese) | (See Japanese page) |
Abstract(in English) | The geometric learning algorithm (GLA) is proposed for an elementary perceptron. The GLA is a modified version of the affine projection algorithm (APA) for adaptive filters. The convergence conditions of the APA and the GLA are different. The convergence condition of the 1st order GLA for 2 patterns is theoretically derived. The new oncept "the angle of the solution area" is introduced. The computer simulation results support that this new concept is a good estimation of the convergence properties. The noise performance of the 1st order GLA is also analyzed. |
Keyword(in Japanese) | (See Japanese page) |
Keyword(in English) | perceptron / pattern classification / neural network / geometric learning algorithm / affine projection algorithm |
Paper # | NC97-5 |
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Committee | NC |
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Conference Date | 1997/5/23(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) | Geometric Learning Algorithm for Elementary Perceptron : Convergence Condition and Noise Performance |
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Keyword(1) | perceptron |
Keyword(2) | pattern classification |
Keyword(3) | neural network |
Keyword(4) | geometric learning algorithm |
Keyword(5) | affine projection algorithm |
1st Author's Name | Seiji MIYOSHI |
1st Author's Affiliation | Graduate School of Natural Science and Technology, Kanazawa Univ.:Department of Electronic Eng., Kobe City College of Technology() |
2nd Author's Name | Kenji NAKAYAMA |
2nd Author's Affiliation | Department of Electrical and Computer Eng., Faculty of Eng., Kanazawa Univ. |
3rd Author's Name | Kazushi IKEDA |
3rd Author's Affiliation | Department of Electrical and Computer Eng., Faculty of Eng., Kanazawa Univ. |
Date | 1997/5/23 |
Paper # | NC97-5 |
Volume (vol) | vol.97 |
Number (no) | 69 |
Page | pp.pp.- |
#Pages | 8 |
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