Nonlinear Dynamics of Complex Neurophysiologic Systems Within a Quantum-Chaos Geometric Approach View Full Text


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Chapter Info

DATE

2021-06-29

AUTHORS

Alexander V. Glushkov , Olga Yu. Khetselius

ABSTRACT

It is presented an advanced, uniform, quantum-chaos-geometric approach to analysis, computing simulation and prediction of a nonlinear dynamics of the complex neurophysiological systemsComplex neurophysiological system (such as the ensembles fluctuations of spontaneous Parkinsonian tremor and fluctuations of the local potential etc.) with elements of a deterministic chaos. The approach is based on the combined application of the complex quantum chaos and dynamical systems theory methods, such as a multi-fractal formalism, mutual information approach, correlation integral analysis, false nearest neighbour algorithm, the Lyapunov exponent’s and Kolmogorov’s entropy analysis, surrogate data method, prediction models, including the neural networks algorithms, algorithms of optimized trajectories etc. It has been numerically studied a chaotic dynamicsNonlinear chaotic dynamics of the complex neurophysiological systemsComplex neurophysiological system (the ensembles fluctuations of spontaneous Parkinsonian tremor and fluctuations of the local potential). New advanced numerical data on topological and dynamical invariants of the system studied, in particular, the correlation, embedding, Kaplan-York dimensions, the Lyapunov exponent’s and Kolmogorov’s entropy etc. are listed and analyzed. More... »

PAGES

291-303

Book

TITLE

Advances in Methods and Applications of Quantum Systems in Chemistry, Physics, and Biology

ISBN

978-3-030-68313-9
978-3-030-68314-6

Identifiers

URI

http://scigraph.springernature.com/pub.10.1007/978-3-030-68314-6_14

DOI

http://dx.doi.org/10.1007/978-3-030-68314-6_14

DIMENSIONS

https://app.dimensions.ai/details/publication/pub.1139212440


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