[formula omitted] fuzzy state estimation for delayed genetic regulatory networks with random gain fluctuations and reaction-diffusion.

In this paper, the problem of H ∞ state estimation for reaction-diffusion genetic regulatory networks under Dirichlet boundary conditions is investigated, where the random gain fluctuations and time-varying delays are taken into consideration. With regard to the existence of disturbance, the H ∞ performance index is introduced to evaluate the capacity of resisting disturbance of the system. Furthermore, the fuzzy-model-based approach is adopted to deal with the nonlinearity of the aforementioned system. The primary objective of the study is to devise a fuzzy state estimator to approximate the concentrations of proteins and mRNAs, such that the states of the error system satisfying H ∞ performance index converge to zero asymptotically. Afterwards, the stability conditions are deduced by virtue of the Lyapunov theory, and the estimator gains are obtained through an effective decoupling method. Ultimately, an example is provided to illustrate the feasibility and validity of the proposed method. [ABSTRACT FROM AUTHOR]