Modeling of a Robust and Fast Noise Cancellation System

Hamed Yaghoobian, A. Khazaei, Mojtaba Salmani Zarchi, S. J. S. Hosayni
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引用次数: 4

Abstract

This paper presents a simple modified modeling of normalized least mean square (NLMS) algorithm with improved convergence speed and inherent robustness at the expense of less granularity for acoustic noise cancelling applications in Simulink environment. The paper further proposes that with an optimal choice of the crucial step size parameter, one can relatively guarantee faster convergence and conditions for robustness. This modification in the system can significantly be applied to any noise cancellation system. The designed system proved to be indubitably successful and functional in performing the intended application that is eliminating noise from a signal such as speech signal or any other type of audio signal. We stimulate the adaptive filter in MATLAB and analyze the performance of the algorithm in terms of convergence speed, computational complexity and stability. The simulation results are included to demonstrate and support the claims and points raised in the paper.
鲁棒快速降噪系统的建模
本文提出了一种简化的归一化最小均方(NLMS)算法的改进模型,该算法在提高收敛速度和固有鲁棒性的同时降低了算法的粒度,可用于Simulink环境下的降噪应用。本文进一步提出了关键步长参数的最优选择,可以相对保证更快的收敛速度和鲁棒性条件。系统中的这种修改可以显著地应用于任何降噪系统。所设计的系统被证明是毫无疑问的成功和功能,在执行预期的应用是消除噪声的信号,如语音信号或任何其他类型的音频信号。在MATLAB中对自适应滤波器进行仿真,并从收敛速度、计算复杂度和稳定性等方面分析了算法的性能。仿真结果验证和支持了本文提出的观点和主张。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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