Abstract
In this paper, the problem of global asymptotic stability of stochastic Markovian jumping reaction-diffusion neural networks with discrete and distributed delays is investigated. By utilizing the Lyapunov–Krasovskii functional method combined with linear matrix inequality approach, novel sufficient stability conditions are derived for impulsive stochastic reaction-diffusion recurrent neural networks with Markovian jumping parameters and mixed delays. Finally, numerical examples with simulation results are given to illustrate the derived theoretical results.
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