Comparing time series using wavelet-based semblance analysis

Cooper, G.R.J.; Cowan, Duncan

doi:10.1016/j.cageo.2007.03.009

Cited by 103 publications

(88 citation statements)

References 5 publications

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“…Correlation and wavelet based semblance analysis (Cooper & Cowan, 2008) were used to compare PRC time traces obtained with fixations and all gaze cases, respectively. Changes in the amplitude level of PRC was tested with the Wilcoxon signed rank sum test (p<0.05).…”

Section: Discussionmentioning

confidence: 99%

Considerations When Calculating Percent Road Centre From Eye Movement Data in Driver Distraction Monitoring

Ahlström

Kircher

2009

Proceedings of the 5th International Driving Symposium on Human Factors in Driver Assessment, Training, and Vehicle Design : Dr

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Summary: Percent road centre (PRC) is a performance indicator which is sensitive to driver distraction. The original definition of PRC is based on fixation data extracted from eye movement recordings, but it has also been suggested that PRC can be determined directly from the gaze data without segmenting it into saccades and fixations. The primary aim of this paper is to investigate if this is the case. Naturalistic driving data from a small scale field operational test comprising seven vehicles was used in the evaluation. It was found that PRC time traces based on gaze data and fixation data, respectively, were highly similar (correlation coefficient=0.95, average wavelet semblance=0.84) except for an absolute amplitude difference of about 8%. This indicates that the two approaches can be used interchangeably and that the processing step of segmenting gaze data into saccades and fixations can be left out. In addition to this finding, design issues related to the calculation of PRC are investigated. Especially, the impact of gaze cases pointing towards the intersection of the road centre area and the centre rear mirror were investigated. Results lead to conclude that gazes and fixations on the centre rear mirror should be removed from the PRC calculations, as they may negatively influence the correctness of the performance indicator.

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Section: Discussionmentioning

confidence: 99%

Considerations When Calculating Percent Road Centre From Eye Movement Data in Driver Distraction Monitoring

Ahlström

Kircher

2009

Proceedings of the 5th International Driving Symposium on Human Factors in Driver Assessment, Training, and Vehicle Design : Dr

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“…While a nonseasonal oscillations of GLDAS HAM excitations are bigger. Looking for correlations between nonseasonal geodetic residuals and other geophysical excitation functions of polar motion, the wavelet-based semblance analysis were used here (Cooper and Cowan, 2008). These semblance filtering compares two datasets based on correlations between their phase angles, as a function of frequency.…”

Section: Multi-annual Variations In Polar Motion Excita-tionsmentioning

confidence: 99%

Hydrological Excitations of Polar Motion Derived from Different Variables of Fgoals − g2 Climate Model

Wińska

2016

Artificial Satellites

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The hydrological contribution to decadal, inter-annual and multi-annual suppress polar motion derived from climate model as well as from GRACE (Gravity Recovery and Climate Experiment) data is discussed here for the period 2002.3-2016.0. The data set used here are Earth Orientation Parameters Combined 04 (EOP C04), Flexible Global Ocean-Atmosphere-Land System Model: Grid-point Version 2 (FGOAL-g2) and Global Land Data Assimilation System (GLDAS) climate models and GRACE CSR RL05 data for polar motion, hydrological and gravimetric excitation, respectively. Several Hydrological Angular Momentum (HAM) functions are calculated here from the selected variables: precipitation, evaporation, runoff, soil moisture, accumulated snow of the FGOALS and GLDAS climate models as well as from the global mass change fields from GRACE data provided by the International Earth Rotation and Reference System Service (IERS) Global Geophysical Fluids Center (GGFC). The contribution of different HAM excitation functions to achieve the full agreement between geodetic observations and geophysical excitation functions of polar motion is studied here.

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“…The semblance S can take on values from −1 to +1. A value of +1 implies perfect anti correlation (Cooper and Cowan, 2008).…”

Section: Wavelet Based Semblancementioning

confidence: 99%

“…This section presents the wavelet based semblance method proposed by Cooper and Cowan (2008) for the interpretation of short period analysis of geomagnetic series related to an earthquake. Wavelet transform operation can characterize the localized structure of time series, which it is possible to analyze in the dimensions of frequency (scale) and position.…”

Section: Wavelet Based Semblancementioning

confidence: 99%

Wavelet Based Semblance and Eigenvalue Analysis for Geomagnetic Variation Related to Micro-Earthquakes in the Korean Peninsula

Ji¹,

Oh²,

Kim³

2012

Journal of the Korean earth science society

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The objective of this paper is to apply a newly developed wavelet-based semblance filtering and eigenvalue analysis to investigate the geomagnetic variations in some micro-earthquakes that had occurred in the Korean Peninsula. The wavelet-based filtering showed improved results in delineating the geomagnetic variations in relation to earthquake events from their background field. In addition, the eigenvalues analysis was also useful for the interpretation of three components geomagnetic fields during the earthquake events. The wavelet-based semblance analysis showed a prominent result for short-term geomagnetic variation related to the earthquake event, and the eigenvalue analysis was feasible to long-term geomagnetic variation. Considering the fact that the basement rock of the Korean Peninsula has a highly resistive electrical structure, it seems to be possible for small magnitude earthquakes to generate some distinguished geomagnetic variations.

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Comparing time series using wavelet-based semblance analysis

Cited by 103 publications

References 5 publications

Considerations When Calculating Percent Road Centre From Eye Movement Data in Driver Distraction Monitoring

Considerations When Calculating Percent Road Centre From Eye Movement Data in Driver Distraction Monitoring

Hydrological Excitations of Polar Motion Derived from Different Variables of Fgoals − g2 Climate Model

Wavelet Based Semblance and Eigenvalue Analysis for Geomagnetic Variation Related to Micro-Earthquakes in the Korean Peninsula

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