Improved time-frequency distribution using singular value decomposition of Choi-Williams distribution

Juan Lu, E. Oruklu, J. Saniie
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引用次数: 3

Abstract

The Choi-Williams distribution (CWD) is an effective time-frequency (TF) distribution to suppress cross-terms. However, one notable drawback of the CWD is that it fails to suppress cross-terms when either center frequencies of two components are close or their time overlap is significant. In this paper, this problem is addressed by reconstructing TF distribution using basis functions which are extracted through Singular Value Decomposition (SVD) from CWD. The numerical analysis of multi-component Gaussian echoes are presented by using SVD of CWD. It is found that this decomposition and reconstruction approach efficiently eliminate residual cross-terms for which the CWD failed to remove. Results are presented in support of exhibiting the effectiveness of SVD of CWD for cross-term suppression.
利用Choi-Williams分布的奇异值分解改进时频分布
Choi-Williams分布(CWD)是抑制交叉项的有效时频分布(TF)。然而,CWD的一个明显缺点是,当两个分量的中心频率接近或它们的时间重叠很大时,它不能抑制交叉项。本文利用基于CWD的奇异值分解(SVD)提取的基函数重构TF分布,解决了这一问题。利用CWD的奇异值分解对多分量高斯回波进行了数值分析。结果表明,这种分解重建方法能够有效地消除CWD无法去除的残留交叉项。研究结果支持了CWD的SVD对交叉期抑制的有效性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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