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Modeling of a Robust and Fast Noise Cancellation System

机译:鲁棒快速噪声消除系统的建模

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摘要

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.
机译:本文提出了一种改进的归一化最小均方算法(NLMS)的简单修改模型,该算法具有提高的收敛速度和固有的鲁棒性,但在Simulink环境中以较小的粒度为代价来消除声学噪声。本文进一步提出,通过对关键步长参数的最佳选择,可以相对保证更快的收敛性和鲁棒性条件。系统中的这种修改可以显着地应用于任何噪声消除系统。事实证明,设计的系统在执行预期的应用中无疑是成功的,并且可以消除语音信号或任何其他类型的音频信号等信号中的噪声。我们在MATLAB中刺激自适应滤波器,并从收敛速度,计算复杂性和稳定性方面分析算法的性能。仿真结果包括在内,以证明和支持本文提出的主张和要点。

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