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Synchronization and prediction of chaotic dynamics on networks of optoelectronic oscillators

dc.contributor.advisorRoy, Rajarshien_US
dc.contributor.advisorMurphy, Thomas Een_US
dc.contributor.authorCohen, Adam B.en_US
dc.description.abstractThe 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.en_US
dc.titleSynchronization and prediction of chaotic dynamics on networks of optoelectronic oscillatorsen_US
dc.contributor.publisherDigital Repository at the University of Marylanden_US
dc.contributor.publisherUniversity of Maryland (College Park, Md.)en_US
dc.subject.pquncontrolledChaotic dynamicsen_US
dc.subject.pquncontrolledComplex systemsen_US
dc.subject.pquncontrolledCoupled oscillatorsen_US
dc.subject.pquncontrolledTime-series predictionen_US

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