文献类型：期刊文献

英文题名：The circuital design of generalized cellular automata for parallel optimization

作者：Shuai, Dianxun[1]; Xu, Li D.[2]; Shuai, Qing[3]; Zhang, Bin[1]

机构：[1] Department of Computer Science and Engineering, East China University of Science and Technology, 200237 Shanghai, China; [2] College of Business and Public Administration, Old Dominion University, Norfolk, VA 23529-0218, United States; [3] Department of Sociology, Huazhong University of Science and Technolog, Wuhan 430074, China

年份：2006

卷号：5

起止页码：3810

外文期刊名：Conference Proceedings - IEEE International Conference on Systems, Man and Cybernetics

收录：EI(收录号：20073510787061)

语种：英文

外文关键词：Computer hardware - Neural networks - Optimization - Parallel processing systems

摘要：The generalized cellular automata (GCA) has the pyramid architecture and the multi-granularity cellular dynamics for effectively solving a class of optimizations problems. In order to further take advantages of GCA, this paper discusses the hardware implementation of GCA with VLSI systolic techniques. In comparison with the Hopfleld-type neural networks and cellular neural networks, the implementation scheme of GCA has features in terms of the much less number of interconnections, the higher-degree optimality, the quicker convergence speed, and the much easier selection of circuital parameters. ? 2006 IEEE.