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引用本文：

路翠华,李国林,谢鑫,等.基于相关特性的改进G-SVSLMS算法[J].电讯技术，2013，53（10）： - . [点击复制]
LU Cui-hua,LI Guo-lin,XIE Xin,et al.Improved G-SVSLMS algorithm based on correlation characteristics[J].，2013，53（10）： - . [点击复制]

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基于相关特性的改进G-SVSLMS算法
路翠华,李国林,谢鑫,奚晓梁
0 字体:加大+\|默认\|缩小-
(海军航空工程学院 7系,山东烟台 264001)

摘要:

为解决改进的基于Sigmoid函数变步长最小均方（G-SVSLMS）算法步长更新公式易受噪声干扰的问题，根据高斯白噪声相关性比较差的特性，对G-SVSLMS算法进行改进，提出基于相关特性的改进G-SVSLMS算法，使算法的抗噪声干扰能力明显增强。理论分析和仿真结果表明：若两算法选取相同参数，则基于相关特性的改进G-SVSLMS算法相对于G-SVSLMS算法具有小的稳态误差；在保证算法收敛的条件下，基于相关特性的改进G-SVSLMS算法相对G-SVSLMS算法具有较快的收敛速度。

关键词: 信号处理噪声抑制 G-SVSLMS算法相关性稳态误差收敛速度

DOI：

基金项目:

Improved G-SVSLMS algorithm based on correlation characteristics

LU Cui-hua,LI Guo-lin,XIE Xin,XI Xiao-liang

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Abstract:

The G-SVSLMS algorithm′s step-formula can be disturbed easily by noise jamming. According to the characteristics that the correlation of white Gaussian noise is bad, improved G-SVSLMS algorithm based on the correlation characteristic is put forward in order to improve G-SVSLMS algorithm′s ability of anti-noise. If two algorithms choose the same parameters, improved G-SVSLMS algorithm based on the correlation characteristics will have less steady-state error than G-SVSLMS algorithm. Under the condition that the two algorithms are convergent, the convergence rate of improved G-SVSLMS algorithm is bigger than that of G-SVSLMS algorithm.Improved G-SVSLMS algorithm′s performance is testified through theoretical analysis and simulation.

Key words: signal processing noise suppression G-SVSLMS algorithm correlation characteristic steady-state error convergence rate