文献类型：期刊文献

中文题名：Area Optimization of Fixed-Polarity Reed-Muller Circuits Based on Niche Genetic Algorithm

英文题名：Area Optimization of Fixed-Polarity Reed-Muller Circuits Based on Niche Genetic Algorithm

作者：Zhang Huihong[1,2];Wang Pengjun[1];Gu Xingsheng[2]

机构：[1]Ningbo Univ, Inst Circuits & Syst, Ningbo 315211, Zhejiang, Peoples R China;[2]E China Univ Sci & Technol, Inst Automat, Shanghai 200237, Peoples R China

年份：2011

卷号：20

期号：1

起止页码：27

中文期刊名：Chinese Journal of Electronics

外文期刊名：CHINESE JOURNAL OF ELECTRONICS

收录：CSTPCD;;EI(收录号：20110713660027);Scopus;WOS:【SCI-EXPANDED(收录号:WOS:000286786500006)】；

基金：Manuscript Received Feb. 2010; Accepted June 2010. This work is supported by the National Natural Science Foundation of China (No.60776022), the Postdoctoral Science Foundation of China (No.20090461355), the Postdoctoral Research Projects of Zhejiang Province, the Scientific Research Fund of Zhejiang Provincial Education Department (No.Y200803880), the Subject Fund of Ningbo University (No.xk109102).

语种：英文

中文关键词：Fixed-polarity RM circuit, Area optimization; Niche technique.

外文关键词：Fixed-polarity RM circuit; Area optimization; Niche technique

摘要：A novel niche genetic algorithm is proposed for area optimization of fixed-polarity Reed-Muller circuits, which may have more than one best polarity. In the algorithm, the niche sources are allocated to a specific number of the most excellent candidates; the niche radius is adjusted according to the real-time information of the evolving process; a flexible memory pool is employed to keep the possibly existed numerous best polarities. Experimental results of eight MCNC benchmark circuits show that the proposed algorithm is superior to the traditional genetic algorithm and the basic clearing algorithm in global searching ability, especially for multi optimal polarities searching.
A novel niche genetic algorithm is proposed for area optimization of fixed-polarity Reed-Muller circuits, which may have more than one best polarity. In the algorithm, the niche sources are allocated to a specific number of the most excellent candidates; the niche radius is adjusted according to the real-time information of the evolving process; a flexible memory pool is employed to keep the possibly existed numerous best polarities. Experimental results of eight MCNC benchmark circuits show that the proposed algorithm is superior to the traditional genetic algorithm and the basic clearing algorithm in global searching ability, especially for multi optimal polarities searching.