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A method of generating intrinsic mode functions through a filtering algorithm based on wavelet packet decomposition

机译:一种通过基于小波包分解的滤波算法生成内部模式功能的方法

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摘要

After a consideration of the previous works on the empirical mode decomposition (EMD) method, we proposed a method to generate intrinsic mode functions (IMFs) through a filtering algorithm based on the wavelet packet decomposition (GIFWPD), and on this basis, performed Hilbert spectrum analysis. The method generates IMFs of which each frequency band has the maximum of width but is not overlapped each other. We adopted the same conditions of IMF from the EMD method as the criterion of IMFs to be generated. But, in the proposed method, the IMFs are generated by a filtering algorithm based on wavelet packet decomposition instead of the sifting process in EMD. Some numerical simulations and comparisons are demonstrated in order to establish the applicability of the method.
机译:在考虑到先前的工作对经验模式分解(EMD)方法之后,我们提出了一种通过基于小波包分解(GIFWPD)的过滤算法来生成内部模式功能(IMF)的方法,并在此基础上进行Hilbert 光谱分析。 该方法产生每个频带的IMF,每个频带的宽度最大但不相互重叠。 我们通过EMD方法采用了与EMD方法相同的IMF条件作为要生成的IMF的标准。 但是,在所提出的方法中,通过基于小波分组分解的滤波算法而不是EMD中的筛选过程来生成IMF。 为了确定该方法的适用性,证明了一些数值模拟和比较。

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