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Please use this identifier to cite or link to this item: http://bura.brunel.ac.uk/handle/2438/3167

Title: Filtering for nonlinear genetic regulatory networks with stochastic disturbances
Authors: Wang, Z
Lam, J
Wei, G
Fraser, K
Liu, X
Keywords: Decay rate
gene expression
genetic regulatory network
stochastic disturbance
time-delay
Publication Date: 2008
Publisher: IEEE
Citation: Automatic Control, IEEE Transactions on. 53 (10) 2448 - 2457
Abstract: In this paper, the filtering problem is investigated for nonlinear genetic regulatory networks with stochastic disturbances and time delays, where the nonlinear function describing the feedback regulation is assumed to satisfy the sector condition, the stochastic perturbation is in the form of a scalar Brownian motion, and the time delays exist in both the translation process and the feedback regulation process. The purpose of the addressed filtering problem is to estimate the true concentrations of the mRNA and protein. Specifically, we are interested in designing a linear filter such that, in the presence of time delays, stochastic disturbances as well as sector nonlinearities, the filtering dynamics of state estimation for the stochastic genetic regulatory network is exponentially mean square stable with a prescribed decay rate lower bound beta. By using the linear matrix inequality (LMI) technique, sufficient conditions are first derived for ensuring the desired filtering performance for the gene regulatory model, and the filter gain is then characterized in terms of the solution to an LMI, which can be easily solved by using standard software packages. A simulation example is exploited in order to illustrate the effectiveness of the proposed design procedures.
URI: http://bura.brunel.ac.uk/handle/2438/3167
ISSN: 0018-9286
Appears in Collections:Computer Science
Dept of Computer Science Research Papers

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