State estimation for neural networks of neutral type with mixed time-varying delays and Markovian jumping parameters∗

This paper is concerned with delay-dependent state estimator for neutral-type neural networks with mixed timevarying delays and Markovian jumping parameters. The addressed neural networks have a finite number of modes, and the modes may jump from one to another according to a Markov process. By construction of a suitable Lyapunov– Krasovskii functional, a delay-dependent condition is developed to estimate the neuron states through available output measurements such that the estimation error system is globally asymptotically stable in mean square. The criterion is formulated in terms of a set of linear matrix inequalities (LMIs), which can be checked efficiently by use of some standard numerical packages.