基于变步长NLMS-Newton算法的多模噪声抑制研究

S. Dalabaev, Chang Liao, A. Muhammad, B. Ahmetov
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引用次数: 0

摘要

现实中存在多模噪声(总体上是非高斯噪声),它对信号造成严重的破坏和损失。传统的LMS算法不能很好地抑制噪声,不仅使收敛速度变慢,而且产生较大的稳态误差和偏移量。本文结合LMS算法和牛顿算法的优点,提出了对自相关矩阵的修正,并采用随信噪比变化的变步长。仿真结果表明,本文提出的算法在收敛速度、稳态误差和偏移量方面都有很大的提高。它还能很好地抑制多模噪声,获取有用的信号。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Research of Multi-mode Noise suppression based on variable step-size NLMS-Newton algorithm
In reality, there are Multi-mode Noise (as a whole, they are non-Gaussian noise), it causes serious damage and loss to the signals. Traditional LMS algorithm can not suppress the noise well, not only slowing down the convergence, but also occurring a big steady-state error and the offset amount. This paper combined with the advantages of LMS algorithm and the Newton algorithm, to propose the amendment of autocorrelation matrix and take variable step-size which changes by the SNR. Simulation results show that the proposed algorithm in this paper has greatly improved in convergence rate, steady state error and the offset amount. It also can well suppress multi-mode noise to take useful signal.
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