State estimation for uncertain Markovian jump neural networks with mixed delays

This paper investigates the problem of state estimation for uncertain Markovian jump neural networks(NNs) with additive time-varying discrete delay components and distributed delay. By constructing a novel Lyapunov–Krasovskii function with multiple integral terms and using an improved inequality, several sufficient conditions are derived. Some improved conditions are formulated in terms of a set of linear matrix inequalities (LMIs), under which the estimation error system is globally exponentially stable in the mean square sense. Some numerical examples are provided to demonstrate the effectiveness of the proposed results.