title: State Estimation for Delayed Genetic Regulatory Networks With Reaction-Diffusion Terms.
abstract: This paper addresses the problem of state estimation for delayed genetic regulatory networks (DGRNs) with reaction-diffusion terms using Dirichlet boundary conditions. The nonlinear regulation function of DGRNs is assumed to exhibit the Hill form. The aim of this paper is to design a state observer to estimate the concentrations of mRNAs and proteins via available measurement techniques. By introducing novel integral terms into the Lyapunov-Krasovskii functional and by employing the Wirtinger-type integral inequality, the convex approach, Green's identity, the reciprocally convex approach, and Wirtinger's inequality, an asymptotic stability criterion of the error system was established in terms of linear matrix inequalities (LMIs). The stability criterion depends upon the bounds of delays and their derivatives. It should be noted that if the set of LMIs is feasible, then the desired observation of DGRNs is possible, and the state estimation can be determined. Finally, two numerical examples are presented to illustrate the availability and applicability of the proposed scheme design.
authors.forename: Xian
authors.initials: X
authors.lastname: Zhang
authors.forename: Yuanyuan
authors.initials: Y
authors.lastname: Han
authors.forename: Ligang
authors.initials: L
authors.lastname: Wu
authors.forename: Yantao
authors.initials: Y
authors.lastname: Wang
mesh_terms: D000465:Algorithms; D000818:Animals; D019295:Computational Biology; D004058:Diffusion; D053263:Gene Regulatory Networks; D006801:Humans; D008957:Models, Genetic; D008962:Models, Theoretical; D016571:Neural Networks, Computer; D013997:Time Factors