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Publication Type : Book Chapter
Publisher : Advances in Intelligent Systems and Computing
Source : Advances in Intelligent Systems and Computing, Springer Verlag, Volume 768, p.217-225 (2019)
ISBN : 9789811306167
Keywords : Chaotic properties, Cognitive behavior, Detrended fluctuation analysis, Differential equations, Fractal dimension, Higuchi fractal dimension, Lyapunov exponent, Lyapunov functions, Lyapunov methods, MATLAB, Mesoscopic levels, Nonlinear analysis, Second-order differential equation, SET modeling, Soft computing, Time series, Time series analysis
Campus : Bengaluru
School : School of Engineering
Department : Electronics and Communication
Year : 2019
Brain signals such as EEG and MEG are the only available dynamical measures of functional status of the brain. Over past several years EEG has been found to have nonlinear and chaotic properties. The nonlinear dynamical measures have been linked to brain functioning including the most complex cognitive behavior of man. Our study focuses on showing evidence of nonlinear chaotic behavior of simulated EEG. We have simulated the EEG at the mesoscopic level by using the biologically realistic Freeman K-sets. Here the behavior of the time series at every level of the olfactory system as modeled in the Freeman-KIII set is obtained by solving a set of second-order differential equations using Euler method in MATLAB. The generated low-dimensional- and high-dimensional time series is subjected to a nonlinear analysis using Higuchi fractal dimension, Lyapunov exponent, and Detrended Fluctuation analysis to validate the chaotic behavior. The study indirectly points to suitability of Freeman model for large-scale brain simulation. © 2019, Springer Nature Singapore Pte Ltd.
Cite this Research Publication : F. Anitta, R. Sunitha, Pradhan, N., and Sreedevi, A., “Non-linear analysis of time series generated from the freeman k-set model”, in Advances in Intelligent Systems and Computing, vol. 768, , Ed. Springer Verlag, 2019, pp. 217-225.