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

beim Graben, P., Drenhaus, H., Brehm, E., Rhode, B., Saddy, D. and Frisch, S. (2007) Enhancing dominant modes in nonstationary time series by means of the symbolic resonance analysis. Chaos, 17 (4). p. 13. ISSN 1054-1500

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To link to this article DOI: 10.1063/1.2795434

Abstract/Summary

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. (c) 2007 American Institute of Physics. (c) 2007 American Institute of Physics.

Item Type:Article
Refereed:Yes
Divisions:Faculty of Life Sciences > School of Psychology and Clinical Language Sciences
ID Code:14159
Uncontrolled Keywords:INDEPENDENT COMPONENT ANALYSIS, EVENT-RELATED FMRI, EVOKED-POTENTIALS, BRAIN POTENTIALS, STOCHASTIC RESONANCE, ELECTROENCEPHALOGRAPHIC DATA, DYNAMICS ANALYSIS, WORKING-MEMORY, PATCH-CLAMP, VARIABILITY

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