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Instantaneous frequency estimation based on synchrosqueezing wavelet transform

机译:基于同步压缩小波变换的瞬时频率估计

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摘要

Recently, the synchrosqueezing transform (SST) was developed as an alternative to the empirical mode decomposition scheme to separate a non-stationary signal with time-varying amplitudes and instantaneous frequencies (IFs) into a superposition of frequency components that each have well-defined IFs. The continuous wavelet transform (CWT)-based SST sharpens the time-frequency representation of a non-stationary signal by assigning the scale variable of the signal's CWT to the frequency variable by a reference IF function. Since the SST method is applied to estimate the IFs of all frequency components of a signal based on one single reference IF function, it may yield not very accurate results. In this paper we introduce the instantaneous frequency-embedded synchrosqueezing wavelet transform (IFE-SST). IFE-SST uses a rough estimation of the IF of a targeted component to produce accurate IF estimation. The reference IF function of IFE-SST is associated with the targeted component Our numerical experiments show that IFE-SST outperforms the CWT-based SST in IF estimation and separation of multicomponent signals.
机译:最近,开发了同步压缩变换(SST)作为经验模式分解方案的替代方案,该方案将具有随时间变化的振幅和瞬时频率(IF)的非平稳信号分离为频率分量的叠加,每个频率分量都有明确的IF 。通过基于参考IF函数将信号CWT的比例变量分配给频率变量,基于连续小波变换(CWT)的SST可以增强非平稳信号的时频表示。由于采用SST方法基于一个参考IF函数估计信号的所有频率分量的IF,因此它可能不会产生非常准确的结果。在本文中,我们介绍了瞬时频率嵌入同步压缩小波变换(IFE-SST)。 IFE-SST使用目标组件的IF的粗略估计来产生准确的IF估计。 IFE-SST的参考IF函数与目标分量相关。我们的数值实验表明,在多分量信号的IF估计和分离中,IFE-SST优于基于CWT的SST。

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