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• W1933689993 abstract "The data missing is a common and important problem in the area of genetic regulatory networks (GRNs). A class of discrete-time GRNs with missing values, parameter uncertainties, time delays and molecular noise is considered in this paper. A set-membership filtering method is proposed to estimate the states of the underlying GRNs. Meanwhile, the corresponding problem of set-membership filtering is formulated as finding the set of estimations that belongs to an ellipsoid. The desired filter gains are characterized as the solution of a set of linear matrix inequalities. Finally, a numerical example is provided to illustrate the effectiveness of the proposed method, which shows that by using the proposed set-membership filtering algorithm, the concentrations of mRNA and protein could be estimated accurately." @default.
• W1933689993 created "2016-06-24" @default.
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• W1933689993 date "2016-01-01" @default.
• W1933689993 modified "2023-09-26" @default.
• W1933689993 title "Set-membership filtering for genetic regulatory networks with missing values" @default.
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• W1933689993 doi "https://doi.org/10.1016/j.neucom.2015.10.083" @default.
• W1933689993 hasPublicationYear "2016" @default.
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