EEG simulation by 2D interconnected chaotic oscillators

Adam Kubany, Ziv Mhabary, Vladimir Gontar

Research output: Contribution to journalArticlepeer-review


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.

Original languageEnglish
Pages (from-to)1-8
Number of pages8
JournalChaos, Solitons and Fractals
Issue number1-3
StatePublished - 1 Jan 2011

ASJC Scopus subject areas

  • General Physics and Astronomy
  • Applied Mathematics
  • Statistical and Nonlinear Physics
  • Mathematical Physics


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