Measuring the complexity of time series: an application to neurophysiological signals.

@article{Andino2000MeasuringTC,
  title={Measuring the complexity of time series: an application to neurophysiological signals.},
  author={S. L. Gonzalez Andino and Rolando Grave de Peralta Menendez and Gregor Thut and Laurent Spinelli and Olaf Blanke and Christoph M. Michel and Margitta Seeck and Theodor Landis},
  journal={Human brain mapping},
  year={2000},
  volume={11 1},
  pages={46-57}
}
Measures of signal complexity can be used to distinguish neurophysiological activation from noise in those neuroimaging techniques where we record variations of brain activity with time, e.g., fMRI, EEG, ERP. In this paper we explore a recently developed approach to calculate a quantitative measure of deterministic signal complexity and information content: The Renyi number. The Renyi number is by definition an entropy, i.e., a classically used measure of disorder in physical systems, and is… CONTINUE READING
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Distrib - uted source models : Standard solutions and new developments

  • R GravedePeraltaMenendez, SL GonzalezAndino
  • 1999

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