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使用连续小波变换和同步挤压变换对时变信号进行分析。

Analysis of time-varying signals using continuous wavelet and synchrosqueezed transforms.

作者信息

Tary Jean Baptiste, Herrera Roberto Henry, van der Baan Mirko

机构信息

Departamento de Geociencias, Universidad de los Andes, Bogotá, Colombia

Department of Physics, University of Alberta, Edmonton, Canada.

出版信息

Philos Trans A Math Phys Eng Sci. 2018 Aug 13;376(2126). doi: 10.1098/rsta.2017.0254.

Abstract

The continuous wavelet transform (CWT) has played a key role in the analysis of time-frequency information in many different fields of science and engineering. It builds on the classical short-time Fourier transform but allows for variable time-frequency resolution. Yet, interpretation of the resulting spectral decomposition is often hindered by smearing and leakage of individual frequency components. Computation of instantaneous frequencies, combined by frequency reassignment, may then be applied by highly localized techniques, such as the synchrosqueezing transform and ConceFT, in order to reduce these effects. In this paper, we present the synchrosqueezing transform together with the CWT and illustrate their relative performances using four signals from different fields, namely the LIGO signal showing gravitational waves, a 'FanQuake' signal displaying observed vibrations during an American football game, a seismic recording of the 8.2 Chiapas earthquake, Mexico, of 8 September 2017, followed by the Irma hurricane, and a volcano-seismic signal recorded at the Popocatépetl volcano showing a tremor followed by harmonic resonances. These examples illustrate how high-localization techniques improve analysis of the time-frequency information of time-varying signals.This article is part of the theme issue 'Redundancy rules: the continuous wavelet transform comes of age'.

摘要

连续小波变换(CWT)在许多不同的科学和工程领域的时频信息分析中发挥了关键作用。它建立在经典的短时傅里叶变换基础之上,但允许可变的时频分辨率。然而,所得频谱分解的解释常常受到各个频率分量的拖尾和泄漏的阻碍。通过频率重分配相结合的瞬时频率计算,然后可以应用高度局部化的技术,如同步挤压变换和ConceFT,以减少这些影响。在本文中,我们介绍了同步挤压变换以及CWT,并使用来自不同领域的四个信号来说明它们的相对性能,这四个信号分别是显示引力波的LIGO信号、显示美国橄榄球比赛期间观测到的振动的“球迷地震”信号、2017年9月8日墨西哥恰帕斯8.2级地震及随后的伊尔玛飓风的地震记录,以及在波波卡特佩特火山记录到的火山地震信号,该信号显示了一次震颤随后是谐波共振。这些例子说明了高局部化技术如何改进对时变信号的时频信息的分析。本文是主题为“冗余规则:连续小波变换走向成熟”的一部分。

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