| Presentation | 1998/5/25 Block Size Optimization for the Block Orthogonal Projection Algorithm Kazushi IKEDA, Seiji MIYOSHI, Kenji NAKAYAMA, |
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| PDF Download Page | PDF download Page Link |
| Abstract(in Japanese) | (See Japanese page) |
| Abstract(in English) | The block orthogonal projection algorithm which is one for transversal filters can be applied to the linear dichotomy (what is called the perceptron) which is nonlinear. When the block size which is the number of examples used in one renewal is one, the algorithm is equivalent to the normalized LMS algorithm and is proven to stop in a finite number of iterations when the learning rate is unity. This report gives the block size which maximizes the convergence speed when the learning rate is unity, and confirms it by computer simulations. The results say that larger block size is not necessarily better. |
| Keyword(in Japanese) | (See Japanese page) |
| Keyword(in English) | Perceptron / Block Orthogonal Projection Algorithm / Convergence Rate |
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| Conference Information | |
| Committee | NC |
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| Conference Date | 1998/5/25(1days) |
| Place (in Japanese) | (See Japanese page) |
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| Topics (in Japanese) | (See Japanese page) |
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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) | Block Size Optimization for the Block Orthogonal Projection Algorithm |
| Sub Title (in English) | |
| Keyword(1) | Perceptron |
| Keyword(2) | Block Orthogonal Projection Algorithm |
| Keyword(3) | Convergence Rate |
| 1st Author's Name | Kazushi IKEDA |
| 1st Author's Affiliation | Grad.Sch.Informatics, Kyoto Univ.() |
| 2nd Author's Name | Seiji MIYOSHI |
| 2nd Author's Affiliation | Kobe City College of Tech. |
| 3rd Author's Name | Kenji NAKAYAMA |
| 3rd Author's Affiliation | Fac.Eng., Kanazawa Univ. |
| Date | 1998/5/25 |
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| Volume (vol) | vol.98 |
| Number (no) | 77 |
| Page | pp.pp.- |
| #Pages | 8 |
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