Extended dissipative analysis of generalized Markovian switching neural networks with two delay components

The topic of delay-dependent extended dissipative analysis for generalized Markovian switching neural networks (GMSNNs) with two delay components is considered in this paper. Based on the concept of the extended dissipativity, this paper is to solve the H∞, L2−L∞, passive and (Q, S, R)- dissipativity performance in a unified framework. By means of an augmented Lyapunov-Krasovskii functional (LKF) as well as employing the novel free-matrix-based inequality and the reciprocally convex approach, some improved delay-dependent criteria are established in terms of linear matrix inequalities (LMIs). Moreover, the obtained criteria are extended to analyze the extended dissipative analysis of generalized neural networks (GNNs) with two delay components. Numerical examples are shown to illustrate the effectiveness of the methods.