Enhancing dominant modes in nonstationary time series by means of the symbolic resonance analysisbeim 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 Full text not archived in this repository. It is advisable to refer to the publisher's version if you intend to cite from this work. See Guidance on citing. To link to this item DOI: 10.1063/1.2795434 Abstract/SummaryWe 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.
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