A New Updating Procedure in the Hopfield-Type Network and Its Application to N-Queens Problem
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概要
- 論文の詳細を見る
When solving combinatorial optimization problems with a binary Hopfield-type neural network, the updating process in neural network is an important step in achieving a solution. In this letter, we propose a new updating procedure in binary Hopfield-type neural network for efficiently solving combinatorial optimization problems. In the new updating procedure, once the neuron is in excitatory state, then its input potential is in positive saturation where the input potential can only be reduced but cannot be increased, and once the neuron is in inhibitory state, then its input potential is in negative saturation where the input potential can only be increased but cannot be reduced. The new updating procedure is evaluated and compared with the original procedure and other improved methods through simulations based on N-Queens problem. The results show that the new updating procedure improves the searching capability of neural networks with shorter computation time. Particularly, the simulation results show that the performance of proposed method surpasses the exiting methods for N-queens problem in synchronous parallel computation model.
- 社団法人電子情報通信学会の論文
- 2002-10-01
著者
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CAO Qi-Ping
Tateyama Systems Institute
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Wang Rong-long
Faculty Of Engineering Toyama University
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WANG Rong-Long
Fuculty of Engineering, TOYAMA University
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TANG Zheng
Fuculty of Engineering, TOYAMA University
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