Enhancing dominant modes in nonstationary time series by means of the symbolic resonance analysis.
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.
beim Graben
Peter
P
School of Psychology and Clinical Language Sciences, University of Reading, Reading RG6 6AH, United Kingdom. p.r.beimgraben@reading.ac.uk
Drenhaus
Heiner
H
Brehm
Eva
E
Rhode
Bela
B
Saddy
Douglas
D
Frisch
Stefan
S
D000328:Adult; D000465:Algorithms; D001921:Brain / Q000473:pathology*; D005071:Evoked Potentials; D005260:Female; D005858:Germany; D006801:Humans; D007802:Language; D008297:Male; D008954:Models, Biological; D015233:Models, Statistical; D008962:Models, Theoretical; D009991:Oscillometry / Q000379:methods; D013269:Stochastic Processes; D013997:Time Factors