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Simulation for noise cancellation using LMS adaptive filter

机译:使用LMS自适应滤波器进行噪声消除仿真

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In this paper, the fundamental algorithm of noise cancellation, Least Mean Square (LMS) algorithm is studied and enhanced with adaptive filter. The simulation of the noise cancellation using LMS adaptive filter algorithm is developed. The noise corrupted speech signal and the engine noise signal are used as inputs for LMS adaptive filter algorithm. The filtered signal is compared to the original noise-free speech signal in order to highlight the level of attenuation of the noise signal. The result shows that the noise signal is successfully canceled by the developed adaptive filter. The difference of the noise-free speech signal and filtered signal are calculated and the outcome implies that the filtered signal is approaching the noise-free speech signal upon the adaptive filtering. The frequency range of the successfully canceled noise by the LMS adaptive filter algorithm is determined by performing Fast Fourier Transform (FFT) on the signals. The LMS adaptive filter algorithm shows significant noise cancellation at lower frequency range.
机译:本文研究了噪声消除,最小均方(LMS)算法的基本算法,并通过自适应滤波器增强。开发了使用LMS自适应滤波算法进行噪声消除的模拟。噪声损坏的语音信号和发动机噪声信号用作LMS自适应滤波算法的输入。将滤波信号与原始无噪声语音信号进行比较,以便突出噪声信号的衰减水平。结果表明,噪声信号由开发的自适应滤波器成功取消。计算无噪声语音信号和滤波信号的差异,结果意味着滤波信号在自适应滤波时接近无噪声语音信号。通过对信号上执行快速傅里叶变换(FFT)来确定LMS自适应滤波器算法的成功取消噪声的频率范围。 LMS自适应滤波算法在较低频率范围内显示出显着的噪声消除。

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