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An Analytical Expression for Empirical Mode Decomposition Based on B-Spline Interpolation

机译:基于B样条插值的经验模式分解的解析表达式。

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Although empirical mode decomposition (EMD) lacks a rigorous theoretical basis, it has attracted much attention for analyzing nonstationary signals adap-tively. In this paper, the EMD method is investigated from a digital signal processing perspective. Based on an analysis of extrema sampling and B-spline interpolation, we show that the upper and lower envelopes of signals are formed by a succession of three basic operations: decimation of local extrema, interpolation, and filtering by a B-spline filter. We then show that some aliasing noise can be suppressed by the mean of the envelopes, though the extrema sampling is a sub-Nyquist sampling. For uniformly spaced extrema of signals, we derive a general analytical expression of intrinsic mode functions (IMFs) extracted by the EMD method from signals.
机译:尽管经验模态分解(EMD)缺乏严格的理论基础,但它已在自适应分析非平稳信号方面引起了广泛关注。本文从数字信号处理的角度研究了EMD方法。基于对极值采样和B样条插值的分析,我们表明信号的上包络和下包络是由以下三个基本操作形成的:局部极值抽取,内插和B样条滤波器的滤波。然后,我们表明,尽管极值采样是次奈奎斯特采样,但通过包络的均值可以抑制某些混叠噪声。对于均匀分布的信号极值,我们导出了通过EMD方法从信号中提取的固有模式函数(IMF)的一般解析表达式。

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