[1]史学军,方金鑫,于舒娟.基于全局人工鱼群算法的盲均衡[J].计算机技术与发展,2013,(05):75-78.
　SHI Xue-jun,FANG Jin-xin,YU Shu-juan.Blind Equalization Based on Global Artificial Fish Swarm Algorithm[J].,2013,(05):75-78.
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基于全局人工鱼群算法的盲均衡()
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《计算机技术与发展》[ISSN:1006-6977/CN:61-1281/TN]

卷:
期数:
2013年05期
页码:
75-78
栏目:
智能、算法、系统工程
出版日期:
1900-01-01

文章信息/Info

Title:
Blind Equalization Based on Global Artificial Fish Swarm Algorithm
文章编号:
1673-629X（2013）05-0075-04
作者:
史学军; 方金鑫; 于舒娟
南京邮电大学 电子科学与工程学院
Author(s):
SHI Xue-jun; FANG Jin-xin; YU Shu-juan
关键词:
盲均衡; 人工鱼群算法; 恒模算法; 代价函数; 适应值
Keywords:
blind equalization; artificial fish swarm algorithm; constant modulus algorithm; cost function; fitness value
文献标志码:
A
摘要:
针对当前盲均衡技术中主要采用的梯度搜索法存在的收敛到局部极小值点问题,提出了一种基于全局人工鱼群算法的盲均衡新算法.基于全局人工鱼群算法的寻优精度高、收敛速度快以及克服局部极值能力强的优点,文中将人工鱼群算法应用于盲均衡算法中,以文献中改进恒模算法的代价函数作为适应值,将均衡器系数作为人工鱼的位置向量,通过算法搜索寻优获得最佳的均衡器系数.通过Matlab7.0实验仿真,结果表明文中提出的算法相对文献中算法具有收敛速度快、码间干扰少的优点
Abstract:
A new blind equalization algorithm based on global artificial fish swarm algorithm (AFSA) is proposed to solve the problem of convergence to local minima in gradient searching method in current blind equalization technologies. Based on some advantages of AF-SA,like high precision of positioning advantage,fast convergence speed and strong capability of overcome local extremum,applies AFSA into blind equalization algorithm and tries to find the optimal equalizer coefficient by searching the optimal in the algorithm using the cost function of modified constant modulus algorithm as fitness value and using coefficient of equalizer as position vector of artificial fish. The experiment results simulated with Matlab 7. 0 shows that this algorithm is an efficient blind equalization algorithm which can increase the convergence speed,reduce inter-symbol interference

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更新日期/Last Update: 1900-01-01