Enhancing dominant modes in nonstationary time series by means of the symbolic resonance analysis

Chaos. 2007 Dec;17(4):043106. doi: 10.1063/1.2795434.

Abstract

We present the symbolic resonance analysis (SRA) as a viable method for addressing the problem of enhancing a weakly dominant mode in a mixture of impulse responses obtained from a nonlinear dynamical system. We demonstrate this using results from a numerical simulation with Duffing oscillators in different domains of their parameter space, and by analyzing event-related brain potentials (ERPs) from a language processing experiment in German as a representative application. In this paradigm, the averaged ERPs exhibit an N400 followed by a sentence final negativity. Contemporary sentence processing models predict a late positivity (P600) as well. We show that the SRA is able to unveil the P600 evoked by the critical stimuli as a weakly dominant mode from the covering sentence final negativity.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Adult
  • Algorithms
  • Brain / pathology*
  • Evoked Potentials*
  • Female
  • Germany
  • Humans
  • Language
  • Male
  • Models, Biological
  • Models, Statistical
  • Models, Theoretical
  • Oscillometry / methods
  • Stochastic Processes
  • Time Factors