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State estimation results for genetic regulatory networks with Lévy-type noise. (English) Zbl 07848593

Summary: In this paper, we investigate some novel results on \(H_\infty\) state estimation for genetic regulatory networks (GRNs) with time-varying delays and Lévy-type noise. The objective of present study is to design the estimator for the considered GRN to analyze the concentrations of mRNAs and proteins through the measured available outputs. The sufficient conditions for stochastic stability of error system is derived by constructing an appropriate Lyapunov-Krasovskii functional (LKF) together with a free-weighing matrix technique and Kunita’s estimate. Further, the results are extended to study \(H_\infty\) state estimation results. Finally, a physical example of transcriptional regulator is considered to show the effectiveness and feasibility of the proposed estimation scheme.

MSC:

92Cxx Physiological, cellular and medical topics
93Dxx Stability of control systems
93Exx Stochastic systems and control
Full Text: DOI

References:

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