Synchronization and prediction of chaotic dynamics on networks of optoelectronic oscillators
Synchronization and prediction of chaotic dynamics on networks of optoelectronic oscillators
Files
Publication or External Link
Date
2011
Authors
Cohen, Adam B.
Advisor
Roy, Rajarshi
Murphy, Thomas E
Murphy, Thomas E
Citation
DRUM DOI
Abstract
The subject of this thesis is the exploration of chaotic synchronization for novel applications including time-series prediction and sensing. We begin by characterizing the nonlinear dynamics of an optoelectronic time-delayed feedback loop. We show that synchronization of an accurate numerical model to experimental measurements provides a way to assimilate data and forecast the future of deterministic chaotic behavior. Next, we implement an adaptive control method that maintains isochronal synchrony for a network of coupled feedback loops when the interaction strengths are unknown and time-varying. Control signals are used as real-time estimates of the variations present within the coupling paths. We analyze the stability of synchronous solutions for arbitrary coupling topologies via a modified master stability function that incorporates the adaptation response dynamics. Finally, we show that the master stability function, which is derived from a set of linearized equations, can also be experimentally measured using a two-node network, and it can be applied to predict the convergence behavior of large networks.