摘要
在分析凸组合最小均方(CLMS)算法性能的基础上,提出一种新的变步长凸组合最小均方(VSCLMS)算法.该算法采用一种变步长滤波器替代原CLMS滤波器组中的恒值大步长滤波器,使新的自适应滤波器能够在噪声、时变,甚至非平稳的环境下保持良好的随动性能,并在收敛的各个阶段均保持快速且稳定的均方特性.理论推导与仿真分析分别验证了新算法与原CLMS算法相比不仅有更快的收敛速度,而且稳态均方性能与跟踪性能也有所提高.
Based on the performance analysis of the CLMS algorithm, a new variable step-size convex combination of leastmean-square (VSCLMS) algorithm was presented.This algorithm proposed a variable step-size adaptive filter to replace one of the original CLMS filters with the constant step-size parameter. Therefore,the new algorithm has a better tracking performance in the presence of noise, time-varying and even non-stable environment. Besides, the new algorithm also has the performance in convergence processing. Theoretical analysis and simulation examples show the new algorithm has validity about the faster convergence and mean-square performance in the steady-state and tracking processing compared with the ClaMS algorithm.
出处
《电子学报》
EI
CAS
CSCD
北大核心
2010年第2期480-484,共5页
Acta Electronica Sinica
基金
国家自然科学基金(No.50974145)
辽宁省自然科学基金(No.20092012)
关键词
自适应滤波
CLMS算法
变步长
凸组合
adaptive filtering
CLMS algorithm
variable step-size
convex combination