Trajectory Tracking of Complex Dynamical Network for Chaos Synchronization Using Recurrent Neural Network
Abstract: In this paper the problem of trajectory tracking is studied. Based on the Lyapunov theory, a control law that achieves the global asymptotic stability of the tracking error between a recurrent neural network and a complex dynamical network is obtained. To illustrate the analytic results we present a tracking simulation of a dynamical network with each node being just one Lorenz´s dynamical system and three identical Chen’s dynamical systems.
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Main Authors: | , , , |
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Format: | Digital revista |
Language: | English |
Published: |
Instituto Politécnico Nacional, Centro de Investigación en Computación
2017
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Online Access: | http://www.scielo.org.mx/scielo.php?script=sci_arttext&pid=S1405-55462017000300485 |
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