光电工程, 2010, 37 (4): 108, 网络出版: 2010-06-13  

IC-PSO 算法的收敛性分析及应用研究

Convergence Analysis of IC-PSO Algorithm and Its Application Research
作者单位
1 燕山大学 信息科学与工程学院,河北 秦皇岛 066004
2 河北大学 电子信息工程学院,河北 保定 071002
摘要
针对标准PSO 算法后期迭代搜索效率不高,容易陷入局部最优的问题,提出将免疫克隆(IC)原理引入PSO算法中,把抗体视为粒子,根据亲和度的高低进行粒子克隆选择、克隆抑制和高频变异,提高了种群的多样性和全局搜索的能力。并将其应用于40 Gb/s 的传输系统中进行了DOP 优化补偿实验,算法补偿所需时间约为71 ms。通过对比补偿前后的信号眼图可以发现,PMD 补偿后,信号眼图张开度有明显改善,证明了算法的有效性。
Abstract
Considering that the standard (Particle Swarm Optimization) PSO algorithm has low iteration efficiency during later period and may trap to local optimum, Immune Clone (IC) principle is introduced into the PSO algorithm. The antibodies can be regarded as the particles. According to the degree of affinity, the clone selection, clone suppression, and high-frequency mutation are performed, which can enhance the diversity of particle swarm and the capability of global searching. The optimal compensation experiment is performed in the 40 Gb/s transmission system, in which the compensation time required was about 71 ms. The opening of signal eye diagram has been improved obviously after compensation. The experimental results demonstrate the effectiveness of the algorithm proposed.

朱奇光, 王洪瑞. IC-PSO 算法的收敛性分析及应用研究[J]. 光电工程, 2010, 37(4): 108. ZHU Qi-guang, WANG Hong-rui. Convergence Analysis of IC-PSO Algorithm and Its Application Research[J]. Opto-Electronic Engineering, 2010, 37(4): 108.

关于本站 Cookie 的使用提示

中国光学期刊网使用基于 cookie 的技术来更好地为您提供各项服务,点击此处了解我们的隐私策略。 如您需继续使用本网站,请您授权我们使用本地 cookie 来保存部分信息。
全站搜索
您最值得信赖的光电行业旗舰网络服务平台!