| 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： |
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| 基金项目: |
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| Improved G-SVSLMS algorithm based on correlation characteristics |
| LU Cui-hua,LI Guo-lin,XIE Xin,XI Xiao-liang |
| () |
| 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 |
