Abstract
This paper presents an exponential synchronization scheme between two chaotic systems with different structures and parameters. A unified model consisting of a linear dynamic system and a bounded static nonlinear operator is employed to describe these totally different chaotic systems. A novel state feedback control law is established to exponentially synchronize the two unified models with different parameters. Most chaotic systems with different structures and parameters, such as Hopfield neural networks, cellular neural networks, Chua’s circuits, unified chaotic systems, Qi systems, and chaotic recurrent multilayer perceptrons, can be transformed into this unified model with the synchronization controller designed in a unified way. Two numerical examples are exploited to illustrate the effectiveness of the proposed design schemes.
| Original language | English |
|---|---|
| Pages (from-to) | 1801-1808 |
| Number of pages | 8 |
| Journal | Neural Computing and Applications |
| Volume | 25 |
| Issue number | 7-8 |
| DOIs | |
| State | Published - Dec 2014 |
| Externally published | Yes |
Keywords
- Different chaotic systems
- Exponential synchronization
- Time delays
- Unified model
Fingerprint
Dive into the research topics of 'Exponential synchronization of two totally different chaotic systems based on a unified model'. Together they form a unique fingerprint.Cite this
- APA
- Author
- BIBTEX
- Harvard
- Standard
- RIS
- Vancouver