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IFESIS: Instantaneous frequencies estimation via subspace invariance properties of wavelet structures

机译:IFESIS:通过小波结构的子空间不变性估计瞬时频率

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摘要

According to the proposed method, a set of wavelet transforms of the signal is first obtained, using a structure of Complex Shifted Morlet Wavelets. No specific constraints are imposed on the center frequencies and the bandwidths of the individual wavelets, as well as on the number of wavelets used. In this way, a set of complex signals result in the time domain, equal to the number of the wavelets used. Then, the instantaneous frequencies of the signals are estimated by applying an appropriate subspace algorithm (as for e.g. ESPRIT), to the entire set of the resulting complex wavelet transforms, exploiting the corresponding subspace rotational invariance property of this set of complex signals. Since the method proposes the application of the subspace algorithm after the signal has been appropriately transformed by an appropriate wavelet structure, contrary to the classical subspace methods which are applied to the signal itself, the desired time-frequency features of the signal are enhanced, while simultaneously, the undesired frequency components, as well as the noise, are suppressed. In this way, the method combines the advantages of the Complex Shifted Morlet Wavelets with the advantages of subspace based approaches. Moreover, the method provides a means for estimating the number of the resulting harmonic components, using as a relevant indicator the number of the non-zero singular values of the corresponding singular value decomposition problem. It should be noted that the resulting singular values are also time dependent, providing valuable information on the possibly time variable dynamic structure of the signal.
机译:根据提出的方法,首先使用复数移位莫雷特小波的结构来获得一组信号的小波变换。对各个子波的中心频率和带宽以及所用子波的数量没有特别的限制。这样,一组复杂的信号在时域产生,等于所使用的小波数。然后,通过利用适当的子空间算法(例如ESPRIT),对整个所得的复数子波变换集合,利用该复信号集合的相应子空间旋转不变性,来估计信号的瞬时频率。由于该方法建议在通过适当的小波结构对信号进行适当的变换之后再应用子空间算法,因此与应用于信号本身的经典子空间方法相反,该信号的所需时频特性得到了增强,而同时,抑制了不希望的频率分量以及噪声。这样,该方法将复数移位莫雷特小波的优点与基于子空间的方法的优点相结合。此外,该方法提供了一种方法,该方法使用相应奇异值分解问题的非零奇异值的数量作为相关指标来估计所得谐波分量的数量。应当注意,所得的奇异值也与时间有关,从而提供了有关信号可能随时间变化的动态结构的有价值的信息。

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