Finite-time H ∞ Filtering for Discrete-time Markovian Jump BAM Neural Networks with Time-varying Delays

This paper deals with the problem of finite-time H∞ filtering for discrete-time Markovian jump BAM neural networks with time-varying delays. To do this, firstly by choosing a suitable Lyapunov function and using Jensen inequality lemma, sufficient criteria are derived to guarantee that the resulting filtering error system is finite-time bounded. And then the gain matrices of the controller and filter are achieved by solving a feasibility problem in terms of linear matrix inequalities with a fixed parameter. Moreover, we assume that disturbances are described by the jumping parameters are generated from discrete-time homogeneous Markov process. Finally a numerical example is presented to show the effectiveness of the proposed method.