An Association Framework to Analyze Dependence Structure in Time Series

  title={An Association Framework to Analyze Dependence Structure in Time Series},
  author={Bilal H. Fadlallah and A. Brockmeier and S. Seth and L. Li and A. Keil and J. Pr{\'i}ncipe},
  journal={2012 Annual International Conference of the IEEE Engineering in Medicine and Biology Society},
  • Bilal H. Fadlallah, A. Brockmeier, +3 authors J. Príncipe
  • Published 2012
  • Computer Science, Medicine
  • 2012 Annual International Conference of the IEEE Engineering in Medicine and Biology Society
  • The purpose of this paper is two-fold: first, to propose a modification to the generalized measure of association (GMA) framework that reduces the effect of temporal structure in time series; second, to assess the reliability of using association methods to capture dependence between pairs of EEG channels using their time series or envelopes. To achieve the first goal, the GMA algorithm was updated so as to minimize the effect of the correlation inherent in the time structure. The reliability… CONTINUE READING
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