首页 | 本学科首页   官方微博 | 高级检索  
     

模拟退火与人工鱼群变异优化的小波盲均衡算法
引用本文:黄 伟,郭业才,王 珍.模拟退火与人工鱼群变异优化的小波盲均衡算法[J].计算机应用研究,2012,29(11):4124-4126.
作者姓名:黄 伟  郭业才  王 珍
作者单位:1. 安徽理工大学 电气与信息工程学院,安徽 淮南,232001
2. 南京信息工程大学 电子与信息工程学院,南京,210044
基金项目:全国优秀博士学位论文作者专项资金资助项目(200753); 安徽省高等学校自然科学基金资助项目(KJ2010A096), 江苏省高等学校自然科学基金资助项目(08KJB510010), 江苏省自然科学基金资助项目(BK2009410).
摘    要:针对人工鱼群算法(AFSA)搜索效率低、易陷入早熟现象等问题,在人工鱼群算法中嵌入变异算子以保持种群多样性,抑制早熟现象,同时引入模拟退火思想增强局部搜索能力,改进算法后期收敛速度减慢的缺点,获得了模拟退火与人工鱼群变异算法;用该算法初始化小波分数间隔盲均衡器的权向量,提出了模拟退火与人工鱼群变异优化的小波分数间隔盲均衡算法(SAFSA-FSE-WTCMA)。水声信道仿真结果表明,新算法具有更快的收敛速度和更小的稳态误差。

关 键 词:盲均衡  模拟退火  人工鱼群算法  水声信道

Orthogonal wavelet transform blind equalization algorithm based on artificial fish swarm optimization of mutation operator and simulated annealing
HUANG Wei,GUO Ye-cai,WANG Zhen.Orthogonal wavelet transform blind equalization algorithm based on artificial fish swarm optimization of mutation operator and simulated annealing[J].Application Research of Computers,2012,29(11):4124-4126.
Authors:HUANG Wei  GUO Ye-cai  WANG Zhen
Affiliation:1. School of Electrical & Information Engineering, Anhui University of Science & Technology, Huainan Anhui 232001, China; 2. College of Electronic & Information Engineering, Nanjing University of Information Science & Technology, Nanjing 210044, China
Abstract:According to disadvantage of the poor local search and premature phenomena of artificial fish swarm algorithm AFSA, AFSA was integrated with mutation operator in order to maintain the population diversity and restrain premature phenomena, it proposed while AFSA was combined with simulated annealing to enhance local search capability and hybrid artificial fish swarm algorithm optimization of mutation operator and simulated annealing. It initialized weight vector of blind equalizer by the algorithm, this paper proposed an orthogonal wavelet transform fractionally spaced blind equalization algorithm based on hybrid artificial fish swarm optimization of mutation operator and simulated annealing. Simulations in underwater acoustic channel demonstrate the proposed algorithm can speed up convergence and decrease state error.
Keywords:bind equalization  simulated annealing  artificial fish swarm algorithm  underwater acoustic channel
本文献已被 CNKI 万方数据 等数据库收录!
点击此处可从《计算机应用研究》浏览原始摘要信息
点击此处可从《计算机应用研究》下载全文
设为首页 | 免责声明 | 关于勤云 | 加入收藏

Copyright©北京勤云科技发展有限公司  京ICP备09084417号