2012
DOI: 10.1142/s0218127412500472
|View full text |Cite
|
Sign up to set email alerts
|

Decay/Growth Rate Estimation Using Instantaneous Lyapunov Exponent

Abstract: The Lyapunov exponent gives a measure of the mean decay/growth rates of the flows of nonlinear systems. However, the Lyapunov exponent needs an infinite time interval of flows and the Jacobian matrix of system dynamics. In this paper, we propose an instantaneous decay/growth rate that is a kind of generalized Lyapunov exponent and call the instantaneous Lyapunov exponent (ILE) with respect to a decay function. The instantaneous Lyapunov exponent is one of the measures that estimate the decay and growth rates o… Show more

Help me understand this report

Search citation statements

Order By: Relevance

Paper Sections

Select...
1
1

Citation Types

0
2
0

Year Published

2018
2018
2024
2024

Publication Types

Select...
3

Relationship

0
3

Authors

Journals

citations
Cited by 3 publications
(2 citation statements)
references
References 8 publications
0
2
0
Order By: Relevance
“…The Lyapunov stability offers precise solutions close to the point of equilibrium of non-linear system. Exponential stability in Lyapunov guarantees a low decay rate which show an estimation of how rapidly the solutions converge (Fichera, 2013;Totoki et al, 2009). Because of that Lyapunov stability criterions have been chosen to analyze and confirm the stability of the offered hybrid controller.…”
Section: Stability Analysis Of Hybrid Controllermentioning
confidence: 99%
“…The Lyapunov stability offers precise solutions close to the point of equilibrium of non-linear system. Exponential stability in Lyapunov guarantees a low decay rate which show an estimation of how rapidly the solutions converge (Fichera, 2013;Totoki et al, 2009). Because of that Lyapunov stability criterions have been chosen to analyze and confirm the stability of the offered hybrid controller.…”
Section: Stability Analysis Of Hybrid Controllermentioning
confidence: 99%
“…x  with infinitesimal differences makes the later values of the s ystem for the two cases n x different [11]. The chaotic behavior is measured with Lyapunov coefficient [12]  which is also a function of the parameter  , positive value of  implies that the system is chaotic, negative value represents stable and periodic system, the case of 0   implies marginally stable orbits.…”
Section: Application In Random Binary Sequencesmentioning
confidence: 99%