Abstract: According to the chaotic features and typical fractional order characteristics of the bearing vibration intensity time series, a forecasting approach based on long range dependence (LRD) is proposed. In order to reveal the internal chaotic properties, vibration intensity time series are reconstructed based on chaos theory in phase-space, the delay time is computed with C-C method and ...

Background: Upright sitting is one of the first developmental motor milestones achieved by infants, and sitting postural sway provides a window into the developing motor control system. A variety of posture sway measures can be used, but the optimal measures for infant development have not been identified. Methods: We have collected sitting postural sway data from two groups of infants, one wit...

We develop a statistical theory of the coupling sensitivity of chaos. The effect was first described by Daido [Prog. Theor. Phys. 72, 853 (1984)]; it appears as a logarithmic singularity in the Lyapunov exponent in coupled chaotic systems at very small couplings. Using a continuous-time stochastic model for the coupled systems we derive a scaling relation for the largest Lyapunov exponent. The ...

We develop a statistical theory of the coupling sensitivity of chaos. The eeect was rst described by Daido Prog. appears as a logarithmic singularity in the Lyapunov exponent in coupled chaotic systems at very small couplings. Using a continuous-time stochastic model for the coupled systems we derive a scaling relation for the largest Lyapunov exponent. The singularity is shown to depend on the...

Lyapunov exponents are an important concept to describe qualitative properties of dynamical systems. For instance, chaotic systems can be caracterized with the positivity of the largest Lyapunov exponent. In this paper, we use the Iwasawa decomposition of the semisimple Lie group Sp(n,R) and the enlargement of the phase space to give a theoretical computation of Lyapunov exponents of almost per...

In this paper, the effect of neuronal gain in discrete delayed neural network model is investigated. It is observed that such neural networks become highly chaotic due to the presence of high neuronal gain. On the basis of the largest Lyapunov exponent and largest eigenvalue of Jacobian matrix, chaos analysis has been done. Finally, some numerical simulations are presented to justify our results.

different discrete models of population dynamics of certain insects have been investigated under various feasible conditions within the framework of nonlinear dynamics. evolutionary phenomena are discussed through bifurcation analysis leading to chaos. some tools of nonlinear dynamics, such as lyapunov characteristic exponents (lce), lyapunov numbers, correlation dimension, etc. are calculated ...