Finite-horizon robust H− filtering for genetic regulatory networks with missing measurements

This paper is concerned with the robust H_∞ filtering problem for the discrete time-varying delayed genetic regulatory networks (GRNs) with missing measurements on the finite horizon. To better approximate the practical GRNs, a discrete model with time-varying parameters is introduced. By appropriately constructing a time-varying Lyapunov function, sufficient criteria in terms of a set of recursive linear matrix inequalities (RLMIs) are obtained firstly under which the filtering error system achieves the prescribed H_∞ performance constraint on the finite horizon. And then the time-varying filter parameter matrices are designed iteratively according to the explicit solutions of the RLMIs. Finally, the effectiveness of the method proposed in this paper is illustrated via a numerical simulation example.