改进自适应对消算法在工业噪声处理中的应用

分析了工业环境噪声的特点,将自适应噪声对消算法应用到工业噪声的处理当中.在传统最小均方(LMS)算法及基于Lorentzian函数的变步长LMS算法的基础上进一步进行约束稳定性条件处理,提出了一种约束稳定性变步长LMS算法,并在Matlab平台上进行了仿真验证.结果表明:算法具有更快的收敛速度以及更小的稳态误差,并且能有效地降低梯度噪声对算法性能的影响.

Application of improved adaptive noise cancellation algorithm in industrial noise processing

The characteristics of industrial environmental noise is analyzed and the adaptive noise cancellation algorithm is applied to the processing of industrial noise. On the basis of traditional least mean square(LMS) algorithm and variable step size LMS algorithm based on Lorentzian function,the constraint stability condition is further processed. A variable step size LMS algorithm for constrained stability is proposed. In order to verify the effectiveness of the algorithm,simulation is carried out on the Matlab platform. And the result show that the proposed algorithm has faster convergence speed and smaller steady-state error. In addition,the influence of gradient noise on the performance of the algorithm is effectively reduced in this algorithm.