Name
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. |
Year | DOI | Venue |
|---|---|---|
2006 | 10.1109/ICSMC.2006.384724 | 2006 IEEE INTERNATIONAL CONFERENCE ON SYSTEMS, MAN, AND CYBERNETICS, VOLS 1-6, PROCEEDINGS |
Keywords | Field | DocType |
integrated circuit design,vlsi,circuit design,neural network,cellular automata,cellular neural network,optimization problem | Convergence (routing),Cellular automaton,Parallel optimization,Computer science,Integrated circuit design,Artificial intelligence,Pyramid,Artificial neural network,Very-large-scale integration,Cellular neural network,Machine learning | Conference |
Volume | Issue | ISSN |
5 | null | 1062-922X |
Citations | PageRank | References |
0 | 0.34 | 0 |
Authors | ||
4 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Dianxun Shuai | 1 | 68 | 22.70 |
| Li D. Xu | 2 | 214 | 19.69 |
| Qing Shuai | 3 | 8 | 5.46 |
| Bin Zhang | 4 | 14 | 4.35 |