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An efficient noise reduction by using diagonal and nondiagonal estimation techniques

机译:利用对角线和非透析估计技术有效降噪

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This paper describes about to reduce the musical noise by diagonal and non-diagonal estimation procedures in time-frequency domain to achieve better SNR of the musical noise signal.State of the art alogorithms parameterized filtering of spectrogaram coefficients with empirically fixed parameters. A block thresholding estimation procedure is introduced, which adjust all parameters adaptively to signal property by minimizing stein estimation of the risk. The resulting algorithm is robust to variations of signal structures such as short transients and long harmonics. Numerical experiments show that this new adaptive estimator is robust to signal type variations and improves the SNR and the perceived quality with respect to diagonal estimator. By this method noise will be more suppressed. For audio time-frequency denoising, we show that block thresholding regularises the estimate and is thus effective in musical noise reduction.
机译:本文介绍了通过时间频域中的对角线和非对角线估计过程来降低音乐噪声,以实现音乐噪声信号的更好的SNR。艺术Alogorithms的艺术校正滤波,具有经验固定的参数的光谱滤波器。引入块阈值估计过程,其通过最小化风险的斯坦坦估计,自适应地调整所有参数。得到的算法对于诸如短瞬变和长谐波的信号结构的变化是鲁棒的。数值实验表明,这种新的自适应估计器对信号类型变化具有鲁棒,并改善了对角估计器的SNR和感知的质量。通过这种方法,将更抑制噪声。对于音频时间频率去噪,我们表明块阈值定律统计估计,因此在音乐降噪中有效。

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