基于梯度下降的自适应音频去噪声的研究
Adaptive Filter for Audio Noise Reduction Basing on Gradient Descent
DOI: 10.12677/CSA.2020.108150, PDF,   
作者: 聂晓鸿:江苏无线电厂,江苏 南京
关键词: 滤波器系数最小均方误差梯度自适应语音噪声Filter Coefficient LMS Gradient Adapt Audio Noise
摘要: 去噪声技术是对音频信号进行适当处理,以补偿噪声畸变的技术,通常把采用自适应去噪声的处理器称为自适应滤波器。本文方案以最小均方误差为准则来计算得到滤波器系数。本文设计了一种采用梯度下降的自适应算法的自适应调整滤波器,根据标准参考信号和混有噪声信号进行自适应滤波运算,迭代递归过程以混有噪声信号与标准参考信号最小均方误差为目标,仿真结果显示这个滤波器可以很好地降低噪声提高信噪比。
Abstract: Filter skill deals with noise in background to compensate channel’s noise and reduce it. Commonly, we call the processor filter. The paper computes filter’s coefficient for minimum variance. The paper advises that one filter can reduce channel’s noise, base on gradient descent .For minimum variance between standard signal and noising signal, the filter’s coefficients will iterate to the last result. The simulation shows the filter can reduce noise to enhance SNR.
文章引用:聂晓鸿. 基于梯度下降的自适应音频去噪声的研究[J]. 计算机科学与应用, 2020, 10(8): 1444-1449. https://doi.org/10.12677/CSA.2020.108150

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