Presentation 1998/2/5
An Optimization Problems Solver using a Neural Network
Aya Suzuki, Kenya Jin'no, Mamoru Tanaka,
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Abstract(in English) This article consider an optimaization problems solver using a neural network. Tank and Hopfield have proposed a linear programming solver with a neural network. The network can seek a minimum of an energy function, but they did not prove that this minimum corresponds to the solution of the problems. In this article, we popopose a novel synthesis procedure which can seek a minimum of a cost function for an optimization problems. Our system does not define the energy function, then the system may have an oscillating state. However, this system guantees that a fixed point corresponds to a minimum of a cost function.
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Keyword(in English) optimization problems / neural networks / fixed point / oscillate
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Committee NC
Conference Date 1998/2/5(1days)
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Registration To Neurocomputing (NC)
Language JPN
Title (in Japanese) (See Japanese page)
Sub Title (in Japanese) (See Japanese page)
Title (in English) An Optimization Problems Solver using a Neural Network
Sub Title (in English)
Keyword(1) optimization problems
Keyword(2) neural networks
Keyword(3) fixed point
Keyword(4) oscillate
1st Author's Name Aya Suzuki
1st Author's Affiliation Department of Electrical Electronic Engineering, Sophia University()
2nd Author's Name Kenya Jin'no
2nd Author's Affiliation Department of Electrical Electronic Engineering, Sophia University
3rd Author's Name Mamoru Tanaka
3rd Author's Affiliation Department of Electrical Electronic Engineering, Sophia University
Date 1998/2/5
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Volume (vol) vol.97
Number (no) 532
Page pp.pp.-
#Pages 6
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