Analog neuro-based approach to tiling problem using fitting function of polyominoes

被引：0

作者：

Ninomiya, Hiroshi ^{[1
]}

Nakayama, Takeshi ^{[1
]}

Asai, Hideki ^{[1
]}

机构：

[1] Department of Systems Engineering, Faculty of Engineering, Shizuoka University, Hamamatsu, 432, Japan

来源：

Electronics and Communications in Japan, Part III: Fundamental Electronic Science (English translation of Denshi Tsushin Gakkai Ronbunshi) | 2000年 / 83卷 / 02期

关键词：

Approximation theory - Computational complexity - Computational geometry - Functions - Mathematical models - Optimization - Parallel algorithms - Problem solving;

D O I：

10.1002/(SICI)1520-6440(200002)83:23.0.CO;2-L

中图分类号：

学科分类号：

摘要：

The tiling problem is a typical NP-complete problem, where the polyominoes are to be arranged without a gap on a finite checkerboard. In this study, the arrangement of l polyominoes on an m × n checkerboard is considered. As the first step, the conventional parallel algorithm using the maximum neural network is verified. Then, the authors propose a solution procedure for the tiling problem, where the analog neural network is used in addition to the fitting function. Lastly, the proposed method and the conventional method are compared, and it is shown that the proposed method is also effective for more complex tiling problems.

引用

页码：1 / 10

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