Presentation | 1999/3/19 Hopfield type Neural Network for Optimization Problems with Linear Constraint Mikiya OOTA, Koichiro YAMAUCHI, Naohiro ISHII, |
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Abstract(in English) | Hopfield type neural networks are usually used to solve optimization problems. Almost all of conventional Hopfield type neural networks change its output vector to minimize a quadratic objective function. Therefore, to solve a constraint optimization problem in the convectional neural network approach, we have to convert the problem into a non-constraint optimization problem using a penalty method. However, the penalty method has a weak point that it has no systematic method to decide penalty parameters. To overcome such drawback, we propose a new method, which is based on the continuous gradient projection method proposed by TANABE. The new method does not need penalty parameters. |
Keyword(in Japanese) | (See Japanese page) |
Keyword(in English) | Hopfield Type Neural Network / Optimization Problem / Karush-Kuhn-Tucker condition / continuous gradient projection method |
Paper # | NC98-164 |
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Committee | NC |
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Conference Date | 1999/3/19(1days) |
Place (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) | Hopfield type Neural Network for Optimization Problems with Linear Constraint |
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Keyword(1) | Hopfield Type Neural Network |
Keyword(2) | Optimization Problem |
Keyword(3) | Karush-Kuhn-Tucker condition |
Keyword(4) | continuous gradient projection method |
1st Author's Name | Mikiya OOTA |
1st Author's Affiliation | Department of Intelligence and Computer Science, Nagoya Institute of Technology() |
2nd Author's Name | Koichiro YAMAUCHI |
2nd Author's Affiliation | Department of Intelligence and Computer Science, Nagoya Institute of Technology |
3rd Author's Name | Naohiro ISHII |
3rd Author's Affiliation | Department of Intelligence and Computer Science, Nagoya Institute of Technology |
Date | 1999/3/19 |
Paper # | NC98-164 |
Volume (vol) | vol.98 |
Number (no) | 674 |
Page | pp.pp.- |
#Pages | 8 |
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