A time-frequency approach for noise reduction
A time-frequency approach for noise reduction
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DOI：
10.1016/j.dsp.2007.09.014
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发表时间：
2008-09-01
影响因子：
2.9
通讯作者：
Hassanpour, Hamid
中科院分区：
文献类型：
--
作者：
Hassanpour, Hamid
本文提出了一种使用时频分布来降低信号时间序列中的噪声的技术。该技术基于与信号的时频表示相关联的矩阵的SVD。该方法首先将信号的时频表示以时频矩阵的奇异值作为空间划分的准则，划分为信号子空间和噪声子空间。由于奇异向量是矩阵的跨度基，因此减少来自奇异向量的噪声的影响并在再现矩阵时使用它们增强了嵌入在信号的时频表示中的信息。该方法利用Savitzky-Golay低通滤波器对奇异向量进行噪声衰减。将该方法应用于合成信号和Newbonn EEG的结果表明，该方法在降低信号噪声方面优于现有方法。(c)2007爱思唯尔公司All rights reserved.
This paper proposes a technique for reducing noise from a signal's time series using a time-frequency distribution. The technique is based on the SVD of the matrix associated with the time-frequency representation of the signal. In this approach the timefrequency representation of the signal is initially divided into signal subspace and noise subspace using singular values of the time-frequency matrix as a criterion for space division. Since singular vectors are the span bases of the matrix, reducing the effect of noise from the singular vectors and using them in reproducing the matrix enhances the information embedded in the timefrequency representation of the signal. The proposed approach utilizes the Savitzky-Golay low-pass filter for noise attenuation from the singular vectors. The results of applying the proposed method on both synthetic signals and newbonn EEGs indicate superiority of the proposed technique over the existing one in reducing noise from signals. (c) 2007 Elsevier Inc. All rights reserved.