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Point-wise dimension estimate of nonstationary, multi-episode, time-series and application to gearbox signal

机译:非平稳,多时间段,时间序列的逐点尺寸估计及其在变速箱信号中的应用

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Dimensions of nonstationary time series is studied. The nonstationarity is considered to be due to multiple episode where an episode is a piece of stationary time series. The dimension estimation algorithms in the literature can be naturally extended to study multi-episode time series by restricting the calculation on data segment of pre-determined length. Inevitably, more than one episode will be included in the segment. This work focuses on finding when such dimension estimate has a local interpretation as the dimension of the episode. It was found that the local interpretation is valid if there is a large enough difference in the autocorrelation time of the episodes. This is termed EES. In practice, the average first passage time of the reconstructed "orbit" can be used to determine EES. Numerical evidence of these results are given and the application to the mechanical gearbox signal are shown.
机译:研究了非平稳时间序列的维数。非平稳性被认为是由于多个情节所致,其中情节是一段固定的时间序列。通过限制对预定长度的数据段的计算,可以自然地将文献中的维估计算法扩展为研究多片段时间序列。不可避免地,该片段中将包含多个情节。这项工作着重于寻找这种维度估计何时具有局部解释作为情节的维度。发现如果情节的自相关时间有足够大的差异,则局部解释是有效的。这称为EES。实际上,重建的“轨道”的平均第一次通过时间可以用来确定EES。给出了这些结果的数值证据,并显示了其在机械变速箱信号中的应用。

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