The Circuital Design of Generalized Cellular Automata for Parallel Optimization

Author

Shuai, Dianxun ; Xu, Li D. ; Shuai, Qing ; Zhang, Bin

Author_Institution

East China Univ. of Sci. & Technol., Shanghai

Volume

5

fYear

2006

fDate

8-11 Oct. 2006

Firstpage

3810

Lastpage

3815

Abstract

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 Hopfield-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.

Keywords

VLSI; cellular automata; integrated circuit design; neural chips; optimisation; Hopfield-type neural network; VLSI systolic technique; cellular neural network; circuital design; generalized cellular automata; hardware implementation; multigranularity cellular dynamics; parallel optimization problem; pyramid architecture; Cellular neural networks; Constraint optimization; Convergence; Cybernetics; Design optimization; Hopfield neural networks; Integrated circuit interconnections; Neural networks; Neurons; Very large scale integration;

fLanguage

English

Publisher

ieee

Conference_Titel

Systems, Man and Cybernetics, 2006. SMC '06. IEEE International Conference on

Conference_Location

Taipei

Print_ISBN

1-4244-0099-6

Electronic_ISBN

1-4244-0100-3

Type

conf

DOI

10.1109/ICSMC.2006.384724

Filename

4274489