Description: 这 里主要对LMS算法及一些改进的LMS算法（NLMS算法、变步长LMS算法、变换域LMS算法）之间的不同点进行了比较，在传统的LMS算法的基础上发 展了LMS算法的应用。另一方面又从RLS算法的分析中对其与LMS算法的不同特性进行了比较。-Here mainly on the LMS algorithm and some improvements of the LMS algorithm (NLMS algorithm, variable step size LMS algorithm, transform domain LMS algorithm) between the different points of comparison, in the traditional LMS algorithm developed on the basis of the application of the LMS algorithm. On the other hand from the analysis of RLS algorithm and LMS algorithm for its different characteristics compared. Platform: |
Size: 30720 |
Author:jj |
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Description: 若不希望用与估计输入信号矢量有关的相关矩阵来加快LMS算法的收敛速度，那么可用变步长方法来缩短其自适应收敛过程，其中一个主要的方法是归一化LMS算法（NLMS算法），变步长 的更新公式可写成
W（n+1）=w（n）+ e（n）x（n）
=w（n）+ （3.1）
式中， = e（n）x（n）表示滤波权矢量迭代更新的调整量。为了达到快速收敛的目的，必须合适的选择变步长 的值，一个可能策略是尽可能多地减少瞬时平方误差，即用瞬时平方误差作为均方误差的MSE简单估计，这也是LMS算法的基本思想。
-Want to estimate if the input signal vector and the relevant matrix to speed up the convergence rate of LMS algorithm, then the variable step size method can be used to shorten its adaptive convergence process, one of the main method is normalized LMS algorithm (NLMS algorithm) , variable step-size update formula can be written W (n+ 1) = w (n)+ e (n) x (n) = w (n)+ (3.1) where, = e (n) x (n) the right to express filter update vector iterative adjust the volume. In order to achieve the purpose of fast convergence, we must choose the appropriate value of variable step size, a possible strategy is as much as possible to reduce the instantaneous squared error, which uses the instantaneous squared error as the mean square error MSE of the simple estimate, which is the basic LMS algorithm思想. Platform: |
Size: 3072 |
Author:闫丰 |
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Description: 本程序对两种固定步长和一种变步长最小均方误差算法的权值收敛进行了仿真，结果表明变步长的算法效果更优。-This programme compare LMS algorithm with VSLMS algorithm. The result indicate that the latter is better. Platform: |
Size: 1024 |
Author:何通 |
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Description: 这里主要对LMS算法及一些改进的LMS算法（NLMS算法、变步长LMS算法、变换域LMS算法）之间的不同点进行了比较，在传统的LMS算法的基础上发展了LMS算法的应用。另一方面又从RLS算法的分析中对其与LMS算法的不同特性进行了比较，很值得研究！-The key players here and some of the LMS algorithm is an improved LMS algorithm (NLMS algorithm, variable step size LMS algorithm, transform domain LMS algorithm) the differences between the points of comparison, in the traditional LMS algorithm is developed on the basis of the LMS algorithm applications. On the other hand and from the analysis of RLS algorithm and LMS algorithm for its different characteristics were compared, it is worth studying! Platform: |
Size: 30720 |
Author:成林 |
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Description: proposes a Verilog implementation of the
Normalized Least Mean Square (NLMS) adaptive algorithm,
having a variable step size. The envisaged application is the
identification of an unknown system. First the convergence of
derived LMS algorithms was analyzed in a Simulink application. Platform: |
Size: 223232 |
Author:陳柏宇 |
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Description: This derivation of the normalised least mean square algorithm is based on Farhang-
Boroujeny 1999, pp.172-175, and Diniz 1997, pp 150-3. To derive the NLMS algorithm
we consider the standard LMS recursion, for which we select a variable step size
parameter, μ(n). This parameter is selected so that the error value , e+(n), will be Platform: |
Size: 6144 |
Author:bahtiar |
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Description: This derivation of the normalised least mean square algorithm is based on Farhang-
Boroujeny 1999, pp.172-175, and Diniz 1997, pp 150-3. To derive the NLMS algorithm
we consider the standard LMS recursion, for which we select a variable step size
parameter, μ(n). This parameter is selected so that the error value , e+(n), will be Platform: |
Size: 1024 |
Author:bahtiar |
Hits:
Description: 这 里主要对LMS算法及一些改进的LMS算法（NLMS算法、变步长LMS算法、变换域LMS算法）之间的不同点进行了比较，，在传统的LMS算法的基础上发 展了LMS算法的应用。另一方面又从RLS算法的分析析中对其与LMS算法的不同特性进行了比较。
-Here the main difference between the LMS algorithm and improved LMS algorithm (NLMS algorithm, variable step size LMS algorithm, the transform domain LMS algorithm) comparison, the traditional LMS algorithm based on the development of the application of the LMS algorithm . On the other hand and from its different characteristics of the LMS algorithm of the analytical analysis of the RLS algorithm. Platform: |
Size: 30720 |
Author:认可 |
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Description: A nonparametric adaptive filtering approach is proposed in this paper. The algorithm is
obtained by exploiting a time-varying step size in the traditional NLMS weight update
equation. The step size is adjusted according to the square of a time-averaging estimate
of the autocorrelation of a priori and a posteriori error. Therefore, the new algorithm has
more effective sense proximity to the optimum solution independent of uncorrelated measurement
noise. Moreover, this algorithm has fast convergence at the early stages of adaptation
and small final misadjustment at steady-state process. It works reliably and is easy
to implement since the update function is nonparametric. Furthermore, the experimental
results in system identification applications are presented to illustrate the principle and
efficiency of the proposed algorithm. Platform: |
Size: 861184 |
Author:mostafa |
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Description: By building the generalized Sigmoid function relationship between normalized step-size and the power of error signal,
a novel variable step-size NLMS algorithm is proposed. It is proved that the step-size of NPVSS-NLMS changes as
the new algorithm does when A=σv
-m and B=2. The physical meanings of the parameters in this algorithm are
explored. The theoretical analysis illustrate that this algorithm combine the virtues of NPVSS-NLMS and Sigmoid
function, and it leads to faster convergence rate and lower final misalignment. The computer simulation results
support the theoretical analysis. Platform: |
Size: 284672 |
Author:mostafa |
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Search - variable step size nlms algorithm