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首页> 外文期刊>Philosophical transactions of the Royal Society. Mathematical, physical, and engineering sciences >Analysis of time-varying signals using continuous wavelet and synchrosqueezed transforms
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Analysis of time-varying signals using continuous wavelet and synchrosqueezed transforms

机译:使用连续小波和同步转换的时变信号分析

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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 M-w 8.2 Chiapas earthquake, Mexico, of 8 September 2017, followed by the Irma hurricane, and a volcano-seismic signal recorded at the Popocatepetl 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.
机译:连续小波变换(CWT)在众多不同领域的时频信息分析中发挥了关键作用。它在经典的短时傅里叶变换中构建,但允许可变时频分辨率。然而,通过涂抹和泄漏各个频率分量的涂抹和泄漏通常阻碍所得光谱分解的解释。然后可以通过高度局部化技术来计算瞬时频率,组合频率重新分配,例如同步识别变换和概念,以减少这些效果。在本文中,我们将Synchroosqueezing变换与CWT一起呈现,并使用来自不同场的四个信号,即表示引力波的Ligo信号,在美式足球比赛期间显示振动的“粉丝”信号,这是一种从不同领域的相对性能。 2017年9月8日墨西哥MW 8.2克拉帕斯地震,其次是IRMA飓风,并在PopocatePetl火山上记录了火山地震信号,显示出震颤,然后进行谐波共振。这些示例说明了如何高定位技术如何改善时变信号的时频信息的分析。

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