采用自适应步长归一化最小均方算法的扩散样条自适应滤波

S. Sitjongsataporn, S. Prongnuch, T. Wiangtong
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引用次数: 0

摘要

提出了基于样条自适应滤波(SAF)的扩散自适应算法,对每个节点采用先组合后适应(CTA)策略。SAF由自适应线性滤波和样条插值函数组成。自适应线性滤波部分给出了归一化最小均方算法。采用自适应平均步长机制对线性滤波部分和非线性滤波部分的拍权向量进行处理,使算法收敛速度快,计算复杂度低。统计结果表明,所提出的扩散算法能够提供与传统扩散策略算法相竞争的结果。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Diffusion Spline Adaptive Filtering with Adaptive Step-size Normalised Least Mean Square Algorithm
Diffusion adaptation on spline adaptive filtering (SAF)is presented with combine-then-adapt (CTA) strategy for each node. SAF consists of an adaptive linear filtering and a spline interpolation function. Normalised least mean square algorithm is furnished in the adaptive linear filtering part. An adaptive averaging step-size mechanism is applied for both tap-weight vector of linear and nonlinear filtering parts to provide the fast convergence with low computation complexity. Statistical results testify that the proposed diffusion algorithm is able to provide promising and competitive results to the conventional diffusion strategy algorithm.
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