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An improved adaptive noise cancelling method

机译:一种改进的自适应噪声消除方法

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摘要

The limitations of Widrow-Hoff's adaptive noise cancelling (ANC) LMS method, in some cases, are discussed and an improved algorithm MLMS is presented. On this basis, the MMLMS algorithm with additional inertia is created and some calculation results by this method are given. It is concluded that the improved LMS algorithm (MLMS) can achieve the goal of noise cancelling by a filter of lower order due to the introduction of delay between signal v/sub 0/(n) and v/sub 1/(n). Compared to the LMS algorithm, the MLMS algorithm speeds up the convergence rate of iteration and remarkably reduces the amount of calculation. With a suitable choice of coefficient /spl alpha/, the MLMS algorithm with inertia term (MMLMS) can also raise the convergence rate of iteration. These algorithms are very useful for acoustic signal analysis.
机译:讨论了Widrow-Hoff自适应噪声消除(ANC)LMS方法的局限性,并提出了一种改进的算法MLMS。在此基础上,建立了具有附加惯性的MMLMS算法,并给出了该方法的一些计算结果。结论是,由于在信号v / sub 0 /(n)和v / sub 1 /(n)之间引入了延迟,因此改进的LMS算法(MLMS)可以实现通过低阶滤波器消除噪声的目的。与LMS算法相比,MLMS算法加快了迭代的收敛速度,并显着减少了计算量。用适当选择系数/ SPL的α/时,MLMS算法与惯性项(MMLMS)也可以提高迭代的收敛速度。这些算法对于声学信号分析非常有用。

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