\(H_\infty\) synchronization of semi-Markovian jump neural networks with randomly occurring time-varying delays
Summary: Based on the Lyapunov stability theory, this paper mainly investigates the \(H_\infty\) synchronization problem for semi-Markovian jump neural networks (semi-MJNNs) with randomly occurring time-varying delays (TVDs). The continuous-time semi-MJNNs, where the transition rates are dependent on sojourn time, are introduced to make the issue under our consideration more general. One of the main characteristics of our work is the handling of TVDs. In addition to using the improved Jensen inequality and the reciprocal convexity lemma to deal with the integral inequality, we also employ Schur complement and the projection lemma to achieve the decoupling between the square term of TVDs. Finally, we verify the validity and feasibility of our method by a couple of simulation examples.
scientific article; zbMATH DE number 6994122
scientific article