A direction optimization least mean square algorithm

被引：0
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作者：
机构：
[1] Department of Automation, University of Science and Technology of China
来源：
Wang, Y. (yongwang@ustc.edu.cn) | 1600年 / Science Press卷 / 36期
关键词：
Adaptive filter; Direction optimization; Direction Optimization Least Mean Square (DOLMS) algorithm; Least Mean Square (LMS) algorithm; Least Mean Square (LMS) ball;
D O I：
10.3724/SP.J.1146.2013.01038
中图分类号：
学科分类号：
摘要：
The update vector of Least Mean Square (LMS) algorithm is an estimation of the gradient vector, thus its convergence rate is limited by the method of steepest descent. Based on the discussion of basic LMS, a direction optimization method of LMS algorithm is proposed in order to get rid of this speed constraint. In the proposed method, the closest update vector to the Newton direction is chosen based on the analysis of the error signal. Based on the method, a Direction Optimization LMS (DOLMS) algorithm is proposed, and it is extended to the variable step-size DOLMS algorithm. The theoretical analysis and the simulation results show that the proposed method has higher speed of convergence and less computational complexity than traditional block LMS algorithm.
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页码：1348 / 1354
页数：6
相关论文
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