Variable Step-Size Block Least Mean Square Adaptive Filters The block LMS algorithms can constitute a major branch in the adaptive algorithms family. In this paper we introduce the new variable step size block least... MSE Abadi,SZ Mousavi,A Hadei - IEEE 被引量: 15发表: 2006年 A ...
图书Least-Mean-Square Adaptive Filters 介绍、书评、论坛及推荐
目录LMS算法概述: LMS主要原理: LMS实现步骤: LMS替代矩阵求逆示例: LMS算法概述: LMS(Least Mean Square),源自LEAST-MEAN-SQUARE ADAPTIVE FILTERS,通过迭代的方式估计出待求参数的最优逼近,常用于滤波。 以为例,, 分别为已知量,为未知量。常规的求解方式即 求得精确解(将看成输入信号,看作未知系统,看作输出...
adaptive filtersfiltering theorycomputational complexityleast-mean squares adaptive filtering techniqueLMS adaptive filtering techniquelow-frequency electromeThe stability of heavily interconnected power systems is a primary concern in the power utility industry. Accurate knowledge of the low-frequency ...
LMS filters are a class of adaptive filters that are able to "learn" an unknown transfer functions. LMS filters use a gradient descent method in which the filter coefficients are updated based on the instantaneous error signal. Adaptive filters are often used in communication systems, equalizers,...
To overcome this problem DA based Least Mean Square (LMS) adaptive filter using offset binary coding (OBC) without LUT is proposed. The proposed method will reduce the logic elements by half when compared to the conventional DA based OBC filter. The Carry Save Accumulator (CSA) is used to ...
Weinbach U, Raziq N & Collier P 2009, 'Mitigation of periodic GPS multipath errors using a normalised least mean square adaptive filter', Journal of Spatial Science, vol. 54, no. 1, pp. 1-13.Weinbach U, Raziq N, Collier P (2009) Mitigation of periodic GPS multipath errors using a ...
filtering theorynoiserecursive estimationstatistical analysisAlthough the normalized least mean square (NLMS) algorithm is robust, it suffers from low convergence... Rupp,M. - 《IEEE Trans Signal Process》 被引量: 206发表: 1998年 Performance analysis of the DCT-LMS adaptive filtering algorithm This ...
A problem commonly encountered in the design of adaptive filters is selection of the step size parameter, μ. In the harmonic reduction problem, a step size parameter μ(n) is used. To evaluate the a posteriori estimation error έ at the nth instant, (11.31)έ(n)=d(n)–w(n+1)Tx...