针对传统NLMS使用固定步长而出现的收敛速度和稳态误差的矛盾,提出一种改进的变步长NLMS算法.该算法建立了步长与误差的函数关系,使步长随着输出误差和噪声误差的变化而动态更新,从而降低稳态误差.理论分析和仿真结果表明,与现有NLMS算法相比,改进的算法具有更快的收敛速度和更低的稳态误差.%Aiming at the contradiction between convergence speed and steady state error of the traditional NLMS,an im-proved variable-step NLMS algorithm is proposed,in which the functional relationship between step-length and error is estab-lished,which makes dynamic update of step length changed with variation of output error and noise error to reduce steady-state error. The theoretical analysis and simulation results show that,compared with the existing NLMS algorithm,the improved algo-rithm has faster convergence speed and lower steady-state error.
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