Presentation | 1995/10/19 A Design Technique of Cellular Neural Networks : Optimaization methods constrained by inequality conditions Koji NAKAI, Akio USHIDA, |
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Abstract(in Japanese) | (See Japanese page) |
Abstract(in English) | We discuss optimization problems constrained by an excess number of linear inequalities, which come from a design of cellular neural networks. In this cases, we introduce a quadratic programming to design the robust template which can find the optimum solution in a closed convex domain only if all of the linear equations constitute the boundaries. However, if it has an excess number of the inequalities, the quadratic programing will sometimes fail to get the optimum solution. In this paper, we propose 3 techniques of simplex method, sign test method and penalty function method. Although first two methods can get the optimum solution, they are inefficiencies for the large systems. The last one can efficiently find the feasible solution in the convex domain. |
Keyword(in Japanese) | (See Japanese page) |
Keyword(in English) | quadratic optimaization / inequality conditions / design of CNN |
Paper # | NLP95-57 |
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Conference Information | |
Committee | NLP |
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Conference Date | 1995/10/19(1days) |
Place (in Japanese) | (See Japanese page) |
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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) | A Design Technique of Cellular Neural Networks : Optimaization methods constrained by inequality conditions |
Sub Title (in English) | |
Keyword(1) | quadratic optimaization |
Keyword(2) | inequality conditions |
Keyword(3) | design of CNN |
1st Author's Name | Koji NAKAI |
1st Author's Affiliation | Dept. of Electronic Control Engineering, Niihama Natioal College of Techology() |
2nd Author's Name | Akio USHIDA |
2nd Author's Affiliation | Dept. of Electrical and Electronic Engineering, Tokushima University |
Date | 1995/10/19 |
Paper # | NLP95-57 |
Volume (vol) | vol.95 |
Number (no) | 296 |
Page | pp.pp.- |
#Pages | 8 |
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