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Maximum neural network with nonlinear self-feedback for maximum clique problem
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DOI：10.1016/j.neucom.2004.01.001.png)
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摘要
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In this paper, by adding a nonlinear self-feedback to the maximum neural network, we propose a parallel algorithm for the maximum clique problem that introduces richer and more flexible dynamics and can prevent the network from getting stuck at local minima. A large number of instances have been simulated to verify the proposed algorithm. (C) 2004 Elsevier B.V. All rights reserved.
Keyword:
maximum clique problem
maximum neural network
nonlinear self-feedback
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期刊
IF:
6.5
论文数:
2.5W
被引数:
6.5W
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