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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)
Perez, J.P. ; Fac. de Cienc. Fisico-Mat., Univ. Autonoma de Nuevo Leon, San Nicolas de los Garza, Mexico ; Gonzalez, J.A. ; Perez, J.

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:

Industrial Electronics, 2009. ISIE 2009. IEEE International Symposium on

Date of Conference:

5-8 July 2009