基于人工免疫网络的正交小波盲均衡算法  

Orthogonal Wavelet Blind Equalization Algorithm Based on Artificial Immune Network

作　　者：郭业才[1] 孙凤[1] 

机构地区：[1]南京信息工程大学电子与信息工程学院,南京210044

出　　处：《计算机工程》2012年第7期158-160,共3页Computer Engineering

基　　金：全国优秀博士学位论文作者专项基金资助项目(200753);安徽省高等学校自然科学基金资助项目(KJ2010A096);江苏省自然科学基金资助项目(BK2009410);江苏省高等学校自然科学基金资助项目(08KJB510010);江苏省六大人才高峰基金资助项目(2008026)

摘　　要：传统的常数模盲均衡算法存在收敛速度慢、均方误差大、易陷入局部极小值点等缺点。为此,提出一种基于人工免疫系统的正交小波盲均衡算法。该算法将均衡器系数向量作为抗体,经过抗体克隆、变异和抑制等操作,搜索到适应度值最高的抗体,即均衡器的最优系数,使权向量跳出局部最优点,接近全局最优点,并利用正交小波变换改善常数模盲均衡算法的收敛性,降低均方误差。仿真实验结果表明,该算法收敛速度快、均方误差小,能得到全局最优解。The traditional constant modulus blind equalization algorithm has some disadvantages such as slow convergence speed,large mean square error,and easily falling into local minimum points.Aiming at these shortcomings,wavelet blind equalization algorithm based on artificial immune system is presented.In the presented algorithm,the equalizer coefficient vector is regarded as antibodies and the optimal solutions can be obtained by replication,mutation and suppression.It can make weight vector escape from local minima and approach the global minima.Its convergence speed can be improved via using orthogonal wavelet transform and its mean-square error can be reduced by artificial immune algorithm.Simulation results show that this presented algorithm has rapid convergence speed,small mean square error and can obtain global optimum solution.

关 键 词：盲均衡 免疫网络 小波 全局收敛 函数优化 常数模算法 

分 类 号：TP18[自动化与计算机技术—控制理论与控制工程]