| Cooperative updating in the Hopfield model. | |
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MedLine Citation:
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PMID: 18249951 Owner: NLM Status: In-Data-Review |
Abstract/OtherAbstract:
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We propose a new method for updating units in the Hopfield model. With this method two or more units change at the same time, so as to become the lowest energy state among all possible states. Since this updating algorithm is based on the detailed balance equation, convergence to the Boltzmann distribution is guaranteed. If our algorithm is applied to finding the minimum energy in constraint satisfaction and combinatorial optimization problems, then there is a faster convergence than those with the usual algorithm in the neural network. This is shown by experiments with the travelling salesman problem, the four-color problem, the N-queen problem, and the graph bi-partitioning problem. In constraint satisfaction problems, for which earlier neural networks are effective in some cases, our updating scheme works fine. Even though we still encounter the problem of ending up in local minima, our updating scheme has a great advantage compared with the usual updating scheme used in combinatorial optimization problems. Also, we discuss parallel computing using our updating algorithm. |
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Authors:
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T Munehisa; M Kobayashi; H Yamazaki |
Publication Detail:
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Type: Journal Article |
Journal Detail:
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Title: IEEE transactions on neural networks / a publication of the IEEE Neural Networks Council Volume: 12 ISSN: 1045-9227 ISO Abbreviation: IEEE Trans Neural Netw Publication Date: 2001 |
Date Detail:
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Created Date: 2008-02-05 Completed Date: - Revised Date: - |
Medline Journal Info:
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Nlm Unique ID: 101211035 Medline TA: IEEE Trans Neural Netw Country: United States |
Other Details:
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Languages: eng Pagination: 1243-51 Citation Subset: - |
Affiliation:
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Faculty of Engineering, Yamanashi University, Kofu, Yamanashi 400-8511, Japan. |
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From MEDLINE®/PubMed®, a database of the U.S. National Library of Medicine
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