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Study of track irregularity time series calibration and variation pattern at unit section.

Jia C, Wei L, Wang H, Yang J - Comput Intell Neurosci (2014)

Bottom Line: Focusing on problems existing in track irregularity time series data quality, this paper first presents abnormal data identification, data offset correction algorithm, local outlier data identification, and noise cancellation algorithms.And then proposes track irregularity time series decomposition and reconstruction through the wavelet decomposition and reconstruction approach.Finally, the patterns and features of track irregularity standard deviation data sequence in unit sections are studied, and the changing trend of track irregularity time series is discovered and described.

View Article: PubMed Central - PubMed

Affiliation: School of Software Engineering, Chongqing University of Posts and Telecommunications, Chongqing 400065, China.

ABSTRACT
Focusing on problems existing in track irregularity time series data quality, this paper first presents abnormal data identification, data offset correction algorithm, local outlier data identification, and noise cancellation algorithms. And then proposes track irregularity time series decomposition and reconstruction through the wavelet decomposition and reconstruction approach. Finally, the patterns and features of track irregularity standard deviation data sequence in unit sections are studied, and the changing trend of track irregularity time series is discovered and described.

Show MeSH
The second layer detail waveform signal of track irregularity (HF).
© Copyright Policy - open-access
Related In: Results  -  Collection


getmorefigures.php?uid=PMC4236969&req=5

fig18: The second layer detail waveform signal of track irregularity (HF).

Mentions: The results of specific decomposition are shown in Figures 17, 18, 19, and 20.


Study of track irregularity time series calibration and variation pattern at unit section.

Jia C, Wei L, Wang H, Yang J - Comput Intell Neurosci (2014)

The second layer detail waveform signal of track irregularity (HF).
© Copyright Policy - open-access
Related In: Results  -  Collection

Show All Figures
getmorefigures.php?uid=PMC4236969&req=5

fig18: The second layer detail waveform signal of track irregularity (HF).
Mentions: The results of specific decomposition are shown in Figures 17, 18, 19, and 20.

Bottom Line: Focusing on problems existing in track irregularity time series data quality, this paper first presents abnormal data identification, data offset correction algorithm, local outlier data identification, and noise cancellation algorithms.And then proposes track irregularity time series decomposition and reconstruction through the wavelet decomposition and reconstruction approach.Finally, the patterns and features of track irregularity standard deviation data sequence in unit sections are studied, and the changing trend of track irregularity time series is discovered and described.

View Article: PubMed Central - PubMed

Affiliation: School of Software Engineering, Chongqing University of Posts and Telecommunications, Chongqing 400065, China.

ABSTRACT
Focusing on problems existing in track irregularity time series data quality, this paper first presents abnormal data identification, data offset correction algorithm, local outlier data identification, and noise cancellation algorithms. And then proposes track irregularity time series decomposition and reconstruction through the wavelet decomposition and reconstruction approach. Finally, the patterns and features of track irregularity standard deviation data sequence in unit sections are studied, and the changing trend of track irregularity time series is discovered and described.

Show MeSH