EEG simulation by 2D interconnected chaotic oscillators

Adam Kubany, Ziv Mhabary and Vladimir Gontar

Chaos, Solitons & Fractals, 2011, vol. 44, issue 1, 1-8

Abstract: An artificial neuronal network composed by 2D interconnected chaotic oscillators is explored for brain waves (EEG) simulation. For the inverse problem solution a parallel real-coded genetic algorithm (PRCGA) is proposed. In order to conduct thorough comparison between the simulated and target signal characteristics, a spectrum analysis of the signals is undertaken. A good matching between the theoretical and experimental EEG signals has been achieved. Numerical results of calculations are presented and discussed.

Date: 2011
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Persistent link: https://EconPapers.repec.org/RePEc:eee:chsofr:v:44:y:2011:i:1:p:1-8

DOI: 10.1016/j.chaos.2010.10.001

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