This control strategy does not require the network to have the same coupling strength on all edges; and for pinned nodes, the ones with the highest degree are selected.
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The illustrative example is composed of a network of 50 nodes; each node dynamics is a Chen chaotic attractor. Two cases are presented. For the first case the whole network tracks a reference for each one of the states; afterwards, the second case uses the backstepping technique to track a desired trajectory for only one state. Tracking performance and dynamical behavior of the controlled network are illustrated via simulations.
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Book Condition:- Brand New. Secured Packaging. Seller Inventory STM More information about this seller Contact this seller. Book Description Condition: New. Seller Inventory n. Condition: New. Language: English. Brand new Book. The first systematic presentation of dynamical evolving networks, with many up-to-date applications and homework projects to enhance study The authors are all very active and well-known in the rapidly evolving field of complex networks Complex networks are becoming an increasingly important area of research Presented in a logical, constructive style, from basic through to complex, examining algorithms, through to construct networks and research challenges of the future.
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Pinning control and synchronization on complex dynamical networks | SpringerLink
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Nature Physics 11, Sagawa and M. Physical Review Letters , Horowitz and S. Non-equilibrium detailed fluctuation theorem for repeated discrete feedback. Physical Review E 82, 5. Horowitz and J. Optimizing non-ergodic feedback engines. Acta Physica Polonica B 44, Horowitz, T. Sagawa and J. The Szilard engine revisited: Entropy, macroscopic randomness, and symmetry breaking phase transitions.