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AF-MNS: A Novel AM-FM Based Measure of Non-Stationarity

机译:AF-MNS:基于新的非实践性的AM-FM措施

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摘要

Robust signal processing in any application depends on the representation and the understanding of the signals in hand. There is a plethora of signal processing methods, wherein choosing a method over others would depend on the attributes of the signals and their intended application. As of now, only spectral stationarity is discussed for the deterministic signals. This letter presents a novel amplitude-modulation-frequency-modulation (AM-FM) based measure of non-stationarity of the deterministic signals by extracting AM-FM components using the Fourier decomposition method (FDM). FDM generates analytic signal representation, where the real and imaginary parts are the Hilbert transform pairs. Simple and intuitive measures of amplitude and frequency non-stationarity are presented to quantitatively assess the extent of non-stationarity. Both these measures are zero for stationary signals, while at least one of them is positive for the non-stationary signals. Important observations regarding the stationarity of a signal are made with the help of some examples. The utility of the concept is demonstrated via an application of EEG signal classification.
机译:在任何应用中的强大信号处理取决于表示手中信号的表示。存在普遍的信号处理方法,其中选择对其他方法的方法取决于信号的属性及其预期应用。截至目前,仅讨论了确定性信号的频谱保同性。本函数通过使用傅立叶分解方法(FDM)提取AM-FM分量,提出了基于新颖的调制 - 频率调制(AM-FM)的确定性信号的非固定性度量。 FDM生成分析信号表示,其中真实和虚部是Hilbert变换对。提出了简单且直观的幅度和频率非公平性,以定量评估非公平性的程度。对于静止信号,这两个措施都是零的,而其中至少一个是非静止信号的阳性。在一些示例的帮助下进行关于信号的实质性的重要观察。通过应用EEG信号分类来证明该概念的效用。

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