Sentence examples for time series distance from inspiring English sources

SAX allows for time series distance measures, which lower bound the corresponding distance measures of the original real-valued series.

Table 3 The distance of the local maximum of the replay30 time series from the start of the respective pulse (inside parentheses) in the ground truth time series Distance of local replay30 maximum (from ground truth start) Lecture A Documentary Cooking S1 33 (40) 58 (1) 45 (105) S1 13 (145) 19 (126) 21 (230) S1 48 (350) 16 (229) −13 (374) S1 1 (554) 15 (338) 21 (475) S1   1 (557)  .

To create a mapping between the two time series, an optimal path is computed over the time-series distance matrix.

Time series of distance profiles monitoring PhC ligand binding during the MD simulations for the PDC109-PhC complex are shown in Fig. 3.

In our experiment, where the extent of the OCT scan is 400 μm (and represents the size of a 10.5 dpc embryonic rat heart) and the imaging plane is rotated by 3° for each time series, the distance between neighboring slices at the radially most distant border is about 10 μm, which is similar to the step used for parallel-slice imaging approaches.

For example, the time series of driving distance and the driving/parking status of vehicles along the day are essential to enable the detailed EV integration researches such as EV day-ahead charging energy planning, EV coordinated scheduling investigation.

The core purpose of the presented approach is to find similarities, i.e., nearest neighbors, of time series by Euclidean distance computation while preserving the privacy of all actors.

If H < 0.5, the time series covers less distance than a random walk.

If H > 0.5, the time series covers larger distance than a random walk.

CPCC can be defined as a measure of the correlation between the Cophenetic distance of two time series objects and the original distance matrix.

We used a novel method of computing the pairwise distance between two time series based on the Mahalanobis Distance derived from the time-series state-space-modeling framework.