A nonparametric VSSNLMS algorithm
A nonparametric VSSNLMS algorithm
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DOI：
10.1109/lsp.2006.876323
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发表时间：
2006-10-01
影响因子：
3.9
通讯作者：
Tressens, Sara
中科院分区：
文献类型：
--
作者：
Benesty, Jacob;Rey, Hernan;Tressens, Sara
变步长归一化最小均方（VSS-NLMS）算法的目的是试图解决NLMS算法快速收敛和低失调的矛盾要求。在文献中可以找到许多VSS-NLMS算法，其中大多数算法都有一个共同点：它们可能不太可靠，因为它们依赖于几个在实践中不易调整的参数。这封信的目的是双重的。首先，我们解释一种简单而优雅的方法来推导VSS-NLMS型算法。其次，提出了一种新的非参数变结构自适应最小均方算法，该算法易于控制，在回声消除中具有良好的性能。
The aim of a variable step size normalized least-mean-square (VSS-NLMS) algorithm is to try to solve the conflicting requirement of fast convergence and low misadjustment of the NLMS algorithm. Numerous VSS-NLMS algorithms can be found in the literature with a common point for most of them: they may not work very reliably since they depend on several parameters that are not simple to tune in practice. The objective of this letter is twofold. First, we explain a simple and elegant way to derive VSS-NLMS-type algorithms. Second, a new nonparametric VSS-NLMS is proposed, that is easy to control and gives good performances in the context of acoustic echo cancellation.