ACTIVE NETWORKS THAT MAXIMIZE THE AMOUNT OF INFORMATION TRANSMISSION

DOI10.1142/S021812741230008XzbMath1270.68037OpenAlexW1990342153WikidataQ58866477 ScholiaQ58866477MaRDI QIDQ2843504

Celso Grebogi, Josué X. de Carvalho, Mahir Saleh Hussein, Murilo S. Baptista

Publication date: 23 August 2013

Published in: International Journal of Bifurcation and Chaos (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1142/s021812741230008x

zbMATH Keywords

informationsynchronizationactive networks

Mathematics Subject Classification ID

Communication networks in operations research (90B18) Network design and communication in computer systems (68M10) Neural networks for/in biological studies, artificial life and related topics (92B20) Communication theory (94A05)

Related Items (1)

Conditional Lyapunov exponents and transfer entropy in coupled bursting neurons under excitation and coupling mismatch

Cites Work

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• Phase and average period of chaotic oscillators
• Upper bounds in phase synchronous weak coherent chaotic attractors
• Non-transitive maps in phase synchronization
• CHARACTERISTIC LYAPUNOV EXPONENTS AND SMOOTH ERGODIC THEORY
• Conditional entropies, phase synchronization and changes in the directionality of information flow in neural systems

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