Abstract
Chaotic maps represent an effective method of generating random-like sequences, that combines the benefits of relying on simple, causal models with good unpredictability. However, since chaotic maps behavior is generally strongly dependent on unavoidable implementation errors and external perturbations, the possibility of guaranteeing map statistical robustness is of great practical concern. Here we present a technique to guarantee the independence of the first-order statistics of external perturbations, modeled as an additive, map-independent random variable. The developed criterion applies to a quite general class of maps. © World Scientific Publishing Company.
Original language | English (US) |
---|---|
Pages (from-to) | 3391-3400 |
Number of pages | 10 |
Journal | International Journal of Bifurcation and Chaos |
Volume | 16 |
Issue number | 11 |
DOIs | |
State | Published - Jan 1 2006 |
Externally published | Yes |
Bibliographical note
Generated from Scopus record by KAUST IRTS on 2023-02-15ASJC Scopus subject areas
- Applied Mathematics
- General
- General Engineering
- Modeling and Simulation