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Stochastic recurent neural control for trajectory tracking of a gene regulatory network biological system

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3 Author(s)
Jose P. Perez ; Facultad de Ciencias, Fisico-Matematicas, Universidad Autonoma de Nuevo Leon, (UANL), San Nicolás de los Garza, Nuevo León, México ; Jorge A. Gonzalez ; Joel Perez

In this paper the problem of trajectory tracking by a stochastic recurrent neural network to a gene regulatory network described by a nonlinear dynamic model is studied. Based on the Lyapunov theory is obtained a control law of that achieves the global asymptotic stability of the tracking error.

Published in:

2009 IEEE International Symposium on Industrial Electronics

Date of Conference:

5-8 July 2009