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引用次数: 11
摘要
自适应消噪是一种众所周知的从受噪声污染的语音中去除噪声的方法。这个问题在很多情况下都会出现,比如飞机驾驶舱和汽车。采用基于信噪比的可变步长参数的归一化最小均方差(NLMS)算法具有良好的收敛速度和较低的稳态失调。本文扩展了调整步长NLMS算法的结果[J]。Kim et al., 2003]通过研究在期望信号和噪声信号存在较大和突然变化时调整步长NLMS算法的方法。仿真结果比较了调整步长NLMS算法与固定步长LMS算法以及其他常用的变步长LMS算法的性能。
Performance analysis of the adjusted step size NLMS algorithm
An adaptive noise canceller is a well-known method for removing noise from noise-corrupted speech. The problem arises in many situations such as airplane cockpits and automobiles. Tire adjusted step size NLMS (normalized least mean squares) algorithm incorporating a variable step size parameter whose values are based on the ratio of signal-to-noise power has very good convergence speed and low steady-state misadjustment. This paper extends the results of the adjusted step size NLMS algorithm [J. Kim et al., 2003] by investigating the adjusted step size NLMS algorithm approaches when large and abrupt changes of the desired signal as well as the noise signal are present. Simulation results are presented to compare the performance of the adjusted step size NLMS algorithm with the fixed step size LMS algorithm and other commonly used variable step size LMS algorithms.