| Issue |
EPL
Volume 103, Number 5, September 2013
|
|
|---|---|---|
| Article Number | 50010 | |
| Number of page(s) | 6 | |
| Section | General | |
| DOI | https://doi.org/10.1209/0295-5075/103/50010 | |
| Published online | 01 October 2013 | |
Global generalized synchronization in networks of different time-delay systems
1 Potsdam Institute for Climate Impact Research - 14473 Potsdam, Germany, EU
2 Centre for Nonlinear Dynamics, School of Physics, Bharathidasan University - Tiruchirapalli 620 024, India
3 Institute of Physics, Humboldt University - 12489 Berlin, Germany, EU
4 Institute for Complex Systems and Mathematical Biology, University of Aberdeen - Aberdeen AB24 3UE, UK, EU
Received: 1 April 2013
Accepted: 4 September 2013
We show that global generalized synchronization (GS) exists in structurally different time-delay systems, even with different orders, with quite different fractal (Kaplan-Yorke) dimensions, which emerges via partial GS in symmetrically coupled regular networks. We find that there exists a smooth transformation in such systems, which maps them to a common GS manifold as corroborated by their maximal transverse Lyapunov exponent. In addition, an analytical stability condition using the Krasvoskii-Lyapunov theory is deduced. This phenomenon of GS in strongly distinct systems opens a new way for an effective control of pathological synchronous activity by means of extremely small perturbations to appropriate variables in the synchronization manifold.
PACS: 05.45.Xt – Synchronization; coupled oscillators / 05.45.Pq – Numerical simulations of chaotic systems / 05.45.-a – Nonlinear dynamics and chaos
© EPLA, 2013
Current usage metrics show cumulative count of Article Views (full-text article views including HTML views, PDF and ePub downloads, according to the available data) and Abstracts Views on Vision4Press platform.
Data correspond to usage on the plateform after 2015. The current usage metrics is available 48-96 hours after online publication and is updated daily on week days.
Initial download of the metrics may take a while.