混合噪声中非线性RLS算法的性能分析

Performance Analysis of Nonlinear RLS in Mixture Noise

本文给出了在混合噪声中非线性递归最小均方误差算法的性能分析 .该算法即是非线性RLS(NRLS) .对残差的饱和处理使用了广义限幅函数 .提出了改进的NRLS均方分析 .计算机数值模拟表明理论分析与模拟结果符合得很好 .根据该分析 ,可以将NRLS的收敛和均方误差表示为非线性函数的斜率和限幅水平的函数 .基于归一化的均方误差 (mse) ,引入了一个辅助变量 ,导出了时变限幅函数 ,加速了收敛并且得到了更小的均方误差 .

This paper presents the performance analysis of recursive least square algorithm with error-saturation in mixture noise. The algorithm is referred to nonlinear RLS (NRLS). Generalized clipping function is considered for the error-saturation nonlinearity. An improved mean square behavior of NRLS is carried out. It is shown that the theoretical analysis and the simulation result are close to each other. From the analysis, we can relate the convergence and the mean square error in terms of the slope and the clipping level of the nonlinear function. Based on the normalized mean square error, an instrumental variable is derived for yielding a variable clipping function to provide fast convergence and small mean square error.