Dissipativity analysis of discrete-time Markovian jumping neural networks with time-varying delays
Muhammed Syed Ali, K. Meenakshi, Nallappan Gunasekaran, Kadarkarai Murugan · The Journal of Difference Equations and Applications · 2018
This paper investigates the problem of dissipativity analysis for discrete-time Markovian jumping neural networks with time-varying delays. Based on an appropriate Lyapunov–Krasovskii functional and by using the latest free-weighting matrix method, a sufficient condition is established to ensure that the neural networks under consideration is strictly (Q, S, R)-γ -dissipative. The derived conditions are presented in terms of linear matrix inequalities. A numerical example is presented to illustrate the effectiveness of the proposed results.