改进的LMS自适应噪声对消算法的应用

摘要

Regarding the characteristics of industrial noise,the adaptive algorithm is applied to the processing of industrial noise.According to the shortcomings of the traditional least mean square (LMS) adaptive algorithm,this paper proposes the algorithm to improve the convergence speed and ensure the smaller steady-state error by constructing the appropriate step factor.It relaxes the constraints of the algorithm to improve the accuracy of step size adjustment.The experimental results show that the proposed algorithm has faster convergence speed,smaller steady-state error and excellent anti-jamming performance compared with other algorithms.%针对工业噪声的特点,将自适应对消算法应用到工业噪声的处理中.根据传统最小均方(Least Mean Square,LMS)自适应算法的缺点,文中通过构造合适的步长因子,引入参数使得算法在提高收敛速度的同时保证较小的稳态误差.放宽算法的约束性条件,以提高步长调整的精度.实验验证,提出的算法与其他算法相比,具有更快的收敛速度、更小的稳态误差以及优良的抗干扰性能.