EconPapers    
Economics at your fingertips  
 

An Optimization Approach for Finding a Spectrum of Lyapunov Exponents

Panos M. Pardalos (), Vitaliy A. Yatsenko (), Alexandre Messo (), Altannar Chinchuluun () and Petros Xanthopoulos ()
Additional contact information
Panos M. Pardalos: University of Florida
Vitaliy A. Yatsenko: University of Florida
Alexandre Messo: Kungliga Tekniska Högskolan
Altannar Chinchuluun: University of Florida
Petros Xanthopoulos: University of Florida

Chapter Chapter 16 in Computational Neuroscience, 2010, pp 285-303 from Springer

Abstract: Abstract In this chapter, we consider an optimization technique for estimating the Lyapunov exponents from nonlinear chaotic systems. We then describe an algorithm for solving the optimization model and discuss the computational aspects of the proposed algorithm. To show the efficiency of the algorithm, we apply it to some well-known data sets. Numerical tests show that the algorithm is robust and quite effective, and its performance is comparable with that of other well-known algorithms.

Keywords: Lyapunov Exponent; Temporal Lobe Epilepsy; Strange Attractor; Lorenz System; Large Lyapunov Exponent (search for similar items in EconPapers)
Date: 2010
References: Add references at CitEc
Citations:

There are no downloads for this item, see the EconPapers FAQ for hints about obtaining it.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:spr:spochp:978-0-387-88630-5_16

Ordering information: This item can be ordered from
http://www.springer.com/9780387886305

DOI: 10.1007/978-0-387-88630-5_16

Access Statistics for this chapter

More chapters in Springer Optimization and Its Applications from Springer
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().

 
Page updated 2025-04-01
Handle: RePEc:spr:spochp:978-0-387-88630-5_16