2015
DOI: 10.1103/physreve.92.012913
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Lyapunov exponent corresponding to enslaved phase dynamics: Estimation from time series

Abstract: A method for the estimation of the Lyapunov exponent corresponding to enslaved phase dynamics from time series has been proposed. It is valid for both nonautonomous systems demonstrating periodic dynamics in the presence of noise and coupled chaotic oscillators and allows us to estimate precisely enough the value of this Lyapunov exponent in the supercritical region of the control parameters. The main results are illustrated with the help of the examples of the noised circle map, the nonautonomous Van der Pole… Show more

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Cited by 9 publications
(8 citation statements)
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“…Indeed, many physiological and physical systems are known to demonstrate the phase synchronization regimes [57][58][59][60][61][62][63][64] or the pre-transitional behavior [32,35,[65][66][67][68]. The found value of zero Lyapunov exponent may be used in these tasks, e.g., as the quantity characterizing the degree of the synchronization [69] to reveal the particularities of the system dynamics depending on the control parameter values.…”
Section: Discussionmentioning
confidence: 99%
“…Indeed, many physiological and physical systems are known to demonstrate the phase synchronization regimes [57][58][59][60][61][62][63][64] or the pre-transitional behavior [32,35,[65][66][67][68]. The found value of zero Lyapunov exponent may be used in these tasks, e.g., as the quantity characterizing the degree of the synchronization [69] to reveal the particularities of the system dynamics depending on the control parameter values.…”
Section: Discussionmentioning
confidence: 99%
“…Moreover, let K = [KǨ], whereK is a scalar. It is easy to show that the control law (15) can be expressed in function of z − k as follows:…”
Section: Dimension Reduction Of the Controlled Hybrid Poincaré Mapmentioning
confidence: 99%
“…Generally, the Lyapunov exponents are used for chaos identification in nonlinear dynamical systems and as a powerful tool for analyzing the stability of nonlinear dynamic systems, especially when the mathematical models of the systems are available. Many research studies focused on the design of numerical methods to estimate the spectrum of Lyapunov exponents or the largest one from time series or data sets [3][4][5][6][7][8][9][10][11][12][13][14][15]. In addition, several papers dealt with the design of numerical/analytical methods for the computation of the spectrum of Lyapunov exponents.…”
Section: Introductionmentioning
confidence: 99%
“…При этом стоит отметить, что разница между критическими значениями параметра связи, соответствующими порогу фазовой синхронизации и моменту перехода показателя Ляпуно-ва в отрицательную область, может быть достаточно большой. Иными словами, условный нулевой показатель Ляпунова оказывается отрица-тельным задолго до возникновения режима фазовой синхронизации, а следовательно, его величина может быть рассмотрена как степень синхронизма перемежающейся фазовой синхронизации, имеющей место на границе возникновения синхронного режима [8][9][10].…”
unclassified
“…D -интенсивность шума, ε и -управляющие параметры), характерной для закритической области значений управляющего пара-метра ε, соответствующей режиму перемежающейся фазовой синхрони-зации [8,9].…”
unclassified