基于sigmoid-sinh分段函数的变步长FxLMS算法

Variable step-size FxLMS algorithm based on sigmoid-sinh piecewise function

为改善滤波-x最小均方(filtered-x least mean square,FxLMS)算法在噪声主动控制时无法兼顾收敛速度和稳态误差的问题,提出了基于sigmoid-sinh分段函数的FxLMS(SSFxLMS)算法,并引入蚁狮算法对SFxLMS(sigmoid filtered-x least mean square)、ShFxLMS(sinh filtered-x least mean square)、SSFxLMS算法的参数进行优化。分别采用高斯白噪声和实测簇绒地毯织机噪声为输入信号,采用FxLMS、SFxLMS、ShFxLMS、SSFxLMS算法进行噪声主动控制仿真,对比分析这4种算法的性能。结果表明:与其他3种算法相比,采用SSFxLMS算法对高斯白噪声和簇绒地毯织机噪声进行控制时,误差信号的平均绝对值更小,平均降噪量与收敛速度也有大幅度提升。由此可知,SSFxLMS算法有效改善了FxLMS算法无法兼顾收敛速度和稳态误差的问题,研究结果为噪声主动控制算法设计提供了一定的参考。

In order to improve the problem that the filtered-x least mean square(FxLMS)algorithm can not give consideration to both the convergence speed and the steady-state error in active noise control,the SSFxLMS algorithm based on sigmoid-sinh subsection function was proposed,and the ant lion algorithm was introduced to optimize the parameters of sigmoid filtered-x least mean square(SFxLMS),sinh filtered-x least mean square(ShFxLMS),and SSFxLMS algorithms.Gaussian white noise and actual tufted carpet loom noise were used as input signals respectively,and FxLMS,SFxLMS,ShFxLMS,SSFxLMS algorithms were used for active noise control simulation,and the performance of these four algorithms was compared and analyzed.The results show that compared with the other three algorithms,when SSFxLMS algorithm is used to control Gaussian white noise and tufted carpet loom noise,the average absolute value of error signal is smaller,and the average noise reduction and convergence speed are also greatly improved.It can be seen that SSFxLMS algorithm effectively improves the problem that FxLMS algorithm can not give consideration to both the convergence speed and the steady-state error.The research results provide a certain reference for the design of active noise control algorithm.