Chinese Physics B, Volume. 29, Issue 8, (2020)
Patterns of cross-correlation in time series: A case study of gait trails
Fig. 1. Intrinsic modes in the records of normal stride intervals for the volunteer numbered 1. “Raw“, the normalized stride interval series.
Fig. 2. The statistical behaviors of the co-occurrences between the IMFs and residue. (a) The histogram of the co-occurrence distribution. (b) The log-log graph of the co-occurrence distribution. The vertical dotted line separates the co-occurrences into two sets, which obey power laws with significantly different scaling exponents.
Fig. 3. The series of mode network (temporal network). A total of 25 mode networks out of the total of 30 ones are displayed. The other five mode networks are not shown, because there all the co-occurrences in them are less than the threshold
Fig. 4. Evolution of the linkages. (a) Each pair of modes is labeled with a specific identification number from 1 to 70, as described in the text part. (b) The evolution of linkage’s weights is displayed with a heat map. The horizontal and vertical axes represent the mode network series
Fig. 5. Evolutionary behavior of the mode network. (a) The global overlapping degree (summation of link’s weights that larger than 0.23) versus the identification number of mode network (time). (b) Average and error for every linkage that are shown in the heat-map in Fig.
Fig. 6. Ego networks for the kernels. The nodes with red color are kernels. The other nodes with deep blue color are alters.
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Jia Song, Tong-Feng Weng, Chang-Gui Gu, Hui-Jie Yang. Patterns of cross-correlation in time series: A case study of gait trails[J]. Chinese Physics B, 2020, 29(8):
Received: Feb. 1, 2020
Accepted: --
Published Online: Apr. 29, 2021
The Author Email: Yang Hui-Jie (hjyang@usst.edu.cn)