Trajectory tracking of complex dynamical network for chaos synchronization using recurrent neural network

Jose P. Perez; Angel Flores H.; Martha S. Lopez de la Fuente

doi:10.13053/cys-21-3-2097

Trajectory tracking of complex dynamical network for chaos synchronization using recurrent neural network

Jose P. Perez, Angel Flores H., Martha S. Lopez de la Fuente

Departamento de Ingeniería

Resultado de la investigación

Resumen

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.

Idioma original	English
Páginas (desde-hasta)	485-492
Número de páginas	8
Publicación	Computacion y Sistemas
Volumen	21
N.º	3
DOI	https://doi.org/10.13053/cys-21-3-2097
Estado	Published - 1 sep 2017

All Science Journal Classification (ASJC) codes

Computer Science(all)

Acceder al documento

10.13053/cys-21-3-2097

Huella Profundice en los temas de investigación de 'Trajectory tracking of complex dynamical network for chaos synchronization using recurrent neural network'. En conjunto forman una huella única.

Citar esto

Perez, J. P., Flores H., A., & Lopez de la Fuente, M. S. (2017). Trajectory tracking of complex dynamical network for chaos synchronization using recurrent neural network. Computacion y Sistemas, 21(3), 485-492. https://doi.org/10.13053/cys-21-3-2097

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