Plant identification via adaptive combination of transversal filters
Plant identification via adaptive combination of transversal filters
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DOI：
10.1016/j.sigpro.2005.11.008
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发表时间：
2006-09
期刊：
影响因子：
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通讯作者：
J. Arenas-García;M. Martínez‐Ramón;Á. Navia-Vázquez;A. Figueiras-Vidal
中科院分区：
文献类型：
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作者：
J. Arenas-García;M. Martínez‐Ramón;Á. Navia-Vázquez;A. Figueiras-Vidal
对于最小均方(LMS)算法的应用，重要的是提高收敛速度与通过为步长选择某个值所带来的残差之间的权衡。在本文中，我们提出了一种混合方法，将两个独立的大小步长的LMS滤波器自适应地组合在一起，在平稳周期内获得快速收敛和低失调。仿真算例表明，与以往的变步长辨识方法相比，该方法是有效的。这种组合方法可以直接扩展到其他类型的滤波器，如递归最小二乘(RLS)滤波器的凸组合所示。
For least mean-square (LMS) algorithm applications, it is important to improve the speed of convergence vs the residual error trade-off imposed by the selection of a certain value for the step size. In this paper, we propose to use a mixture approach, adaptively combining two independent LMS filters with large and small step sizes to obtain fast convergence with low misadjustment during stationary periods. Some plant identification simulation examples show the effectiveness of our method when compared to previous variable step size approaches. This combination approach can be straightforwardly extended to other kinds of filters, as it is illustrated with a convex combination of recursive least-squares (RLS) filters.