一种基于四阶统计量的递推LMS算法  

A Recursive Least Mean Sqare Algorithm Based on Fourth-Order Statistics

作　　者：陶然[1] 张卫强[1] 马永锋[1] 

机构地区：[1]北京理工大学信息科学技术学院电子工程系,北京100081

出　　处：《北京理工大学学报》2004年第5期442-445,共4页Transactions of Beijing Institute of Technology

基　　金：国家自然科学基金资助项目(60232010);高等学校优秀青年教师教学科研奖励计划资助

摘　　要：提出一种基于四阶统计量一维切片的LMS算法,并且给出其递推形式.该算法能够有效地抑制相关高斯噪声的影响,性能优于传统的基于相关的LMS算法;递推形式降低了其计算复杂度,能够满足实时处理的要求.采用相关高斯色噪声进行数值仿真,结果表明该方法的有效性.该算法可在雷达、声纳及通信系统中用于多径系数估计.An LMS algorithm based on one dimensional slice of fourth-order statistics is proposed and its recursive form is given. This algorithm can suppress the correlated Gaussian noises effectively, and its performance is better than the conventional autocorrelation-based LMS algorithm. The recursive form reduces the computational complexity, and it can meet the need of real-time processing. Simulation results are presented to demonstrate the effectiveness of this approach. The presented algorithm can be used to estimate multi-path coefficients in radar, sonar and communication systems.

关 键 词：LMS算法 高阶统计量 递推形式 

分 类 号：TN957.51[电子电信—信号与信息处理] TN911.72[电子电信—信息与通信工程]