What is it about?
Adaptive dynamical networks are among the most advanced and challenging natural and technical objects, with the brain being a prominent example. These networks have plasticity mechanisms that allow for learning, repairing damaged parts, and other important features. One key feature of adaptive networks is their ability to flexibly adapt their structure to perform specific functions.
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Why is it important?
In our work, we demonstrate how these adaptive networks can adjust their structure temporally to either synchronize or desynchronize, leading to recurrent emergence of synchronization or desynchronization.
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This page is a summary of: Asymmetric adaptivity induces recurrent synchronization in complex networks, Chaos An Interdisciplinary Journal of Nonlinear Science, February 2023, American Institute of Physics,
DOI: 10.1063/5.0128102.
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