TY - JOUR
T1 - Trajectory tracking of complex dynamical network for chaos synchronization using recurrent neural network
AU - Perez, Jose P.
AU - Flores H., Angel
AU - Lopez de la Fuente, Martha S.
PY - 2017/9/1
Y1 - 2017/9/1
N2 - 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.
AB - 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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U2 - 10.13053/cys-21-3-2097
DO - 10.13053/cys-21-3-2097
M3 - Article
VL - 21
SP - 485
EP - 492
JO - Computacion y Sistemas
JF - Computacion y Sistemas
SN - 1405-5546
IS - 3
ER -