有源噪声主动控制中一种改进的变步长算法研究

An Improved Variable Step Size Least Mean Square Algorithm for Active Noise Control

在噪声有源抑制(ANC)技术中,自适应控制算法的核心是基于最小均方误差的信号跟踪问题,传统算法对提高收敛速度和减小稳态误差不能兼顾。本文提出了一种改进的变步长算法(IVssLMS),该算法可以在保证稳态误差的同时,有效拓宽计算步长的调节范围,提高计算的迭代收敛速率。仿真试验证明了算法的有效性。

In active noise control （ANC） system, the least mean square method based adaptive control algorithm is commonly used to trace the noisy signal. However, the traditional strategy could hardly attend increasing convergence speed and decreasing the steady error simultaneously. This paper proposes an improved variable step size least mean square （IVssLMS）, which can enlarge the calculating step and so raise the calculating rate while still assure to contemporize limiting the steady error and improving the convergence performance. Simulation results have denoted the efficiency of the proposed algorithm.