Computing the Kolmogorov entropy from time signals of dissipative and conservative dynamical systems

1985 ◽  
Vol 31 (3) ◽  
pp. 1872-1882 ◽  
Author(s):  
Aviad Cohen ◽  
Itamar Procaccia
1982 ◽  
Vol 120 ◽  
pp. 155-183 ◽  
Author(s):  
Jon Lee

We have investigated a sequence of dynamical systems corresponding to spherical truncations of the incompressible three-dimensional Navier-Stokes equations in Fourier space. For lower-order truncated systems up to the spherical truncation of wavenumber radius 4, it is concluded that the inviscid Navier-Stokes system will develop mixing (and a fortiori ergodicity) on the constant energy-helicity surface, and also isotropy of the covariance spectral tensor. This conclusion is, however, drawn not directly from the mixing definition but from the observation that one cannot evolve the trajectory numerically much beyond several characteristic corre- lation times of the smallest eddy owing to the accumulation of round-off errors. The limited evolution time is a manifestation of trajectory instability (exponential orbit separation) which underlies not only mixing, but also the stronger dynamical charac- terization of positive Kolmogorov entropy (K-system).


1998 ◽  
Vol 08 (09) ◽  
pp. 1839-1842 ◽  
Author(s):  
K. Pyragas

Secure communication via chaotic synchronization is demonstrated using dynamical systems governed by delay deferential equations. Strange attractors of such systems can have an arbitrarily large number of positive Lyapunov exponents giving rise to very complex time signals. This features can provide high security of masked messages.


2019 ◽  
Vol 69 (1) ◽  
pp. 139-146
Author(s):  
Mehdi Rahimi

Abstract In this paper, we introduce the concept of entropy kernel operator for compact dynamical systems of finite Kolmogorov entropy. It is a compact positive operator on a Hilbert space. Then we state the Kolmogorov entropy in terms of the eigenvalues of the entropy kernel operator.


2008 ◽  
Vol 18 (09) ◽  
pp. 2851-2855 ◽  
Author(s):  
VADIM S. ANISHCHENKO ◽  
SERGEY ASTAKHOV

The mixing property is characterized by the metric entropy that is introduced by Kolmogorov for dynamical systems. The Kolmogorov entropy is infinite for a stochastic system. In this work, a relative metric entropy is considered. The relative metric entropy allows to estimate the level of mixing in noisy dynamical systems. An algorithm for calculating the relative metric entropy is described and examples of the metric entropy estimation are provided for certain chaotic systems with various noise intensities. The results are compared to the entropy estimation given by the positive Lyapunov exponents.


2001 ◽  
Vol 01 (02) ◽  
pp. R131-R149 ◽  
Author(s):  
MARIA K. KOLEVA ◽  
VALÉRY C. COVACHEV

The major goal of the present paper is to find out the manifestation of the boundedness of fluctuations. Two different subjects are considered: (i) an ergodic Markovian process associated with a new type of large scale fluctuations at spatially homogeneous reaction systems; (ii) simulated dynamical systems that possess strange attractors. Their common property is that the fluctuations are bounded. It is found out that the mathematical description of the stochasticity at both types of systems is identical. Then, it is to be expected that it exhibits certain common features whose onset is the stochasticity, namely: (i) The power spectrum of a time series of length T comprises a striclty decreasing band that uniformly fits the shape 1/fα(f) where [Formula: see text] and α(f) strictly increases to the value α(∞) = p(p > 2) as f. approaches infinity. Practically, at low frequencies this shape is 1/f-like with high accuracy because the deviations of the non-constant exponent α(f) from 1 are very small and become even smaller as the frequency tends to 1/T. The greatest advantage of the shape 1/fα(f) is that it ensures a finite variance of fluctuations. (ii) It is found out that the structure of a physical and a strange attractor is identical and they are non-homogeneous. (iii) The Kolmogorov entropy is finite.


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