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Empirical mode decomposition apparatus, method and article of manufacture for analyzing biological signals and performing curve fitting

机译:用于分析生物信号并进行曲线拟合的经验模态分解装置,方法和制品

摘要

A computer implemented physical signal analysis method includes four basic steps and the associated presentation techniques of the results. The first step is a computer implemented Empirical Mode Decomposition that extracts a collection of Intrinsic Mode Functions (IMF) from nonlinear, nonstationary physical signals. The decomposition is based on the direct extraction of the energy associated with various intrinsic time scales in the physical signal. Expressed in the IMF's, they have well-behaved Hilbert Transforms from which instantaneous frequencies can be calculated. The second step is the Hilbert Transform which produces a Hilbert Spectrum. Thus, the invention can localize any event on the time as well as the frequency axis. The decomposition can also be viewed as an expansion of the data in terms of the IMF's. Then, these IMF's, based on and derived from the data, can serve as the basis of that expansion. The local energy and the instantaneous frequency derived from the IMF's through the Hilbert transform give a full energy-frequency-time distribution of the data which is designated as the Hilbert Spectrum. The third step filters the physical signal by combining a subset of the IMFs. In the fourth step, a curve may be fitted to the filtered signal which may not have been possible with the original, unfiltered signal.
机译:计算机实现的物理信号分析方法包括四个基本步骤以及相关的结果表示技术。第一步是计算机执行的经验模式分解,该过程从非线性的非平稳物理信号中提取本征函数(IMF)的集合。分解基于与物理信号中各种固有时间尺度相关的能量的直接提取。它们以IMF表示,具有良好的Hilbert变换,可以从中计算出瞬时频率。第二步是产生希尔伯特频谱的希尔伯特变换。因此,本发明可以在时间以及频率轴上定位任何事件。分解也可以看作是根据IMF数据的扩展。然后,这些基于数据并从数据派生的IMF可以用作扩展的基础。从国际货币基金组织通过希尔伯特变换得到的局部能量和瞬时频率给出了数据的完整能量-频率-时间分布,称为希尔伯特频谱。第三步,通过组合IMF的子集来过滤物理信号。在第四步骤中,可以将曲线拟合到滤波后的信号,这对于原始未滤波信号可能是不可能的。

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