Proceedings of the IEEK Conference (대한전자공학회:학술대회논문집)

The Institute of Electronics and Information Engineers (대한전자공학회)
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A Dynamical N-Queen Problem Solver using Hysteresis Neural Networks

  • Yamamoto, Takao (Department of Electrical and Electronics Engineering, Faculty of Engineering, Nippon Institute of Techonology) ;
  • Jin′no, Kenya (Department of Electrical and Electronics Engineering, Faculty of Engineering, Nippon Institute of Techonology) ;
  • Hirose, Haruo (Department of Electrical and Electronics Engineering, Faculty of Engineering, Nippon Institute of Techonology)
  • Published : 2002.07.01
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Abstract

In previous study about combinatorial optimization problem solver by using neural network, since Hopfield method, to converge into the optimum solution sooner and certainer is regarded as important. Namely, only static states are considered as the information. However, from a biological point of view, the dynamical system has lately attracted attention. Then we propose the "dynamical" combinatorial optimization problem solver using hysteresis neural network. In this article, the proposal system is evaluated by the N-Queen problem.

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