In this paper, the stability problem is studied for a class of stochastic neutral-type neural networks with Markovian jumping parameters. By using fixed point theorem, the existence and uniqueness of solution for the neural networks system are obtained. Furthermore, based on the Lyapunov-Krasovskii functional, a linear matrix inequality (LMI) approach is developed to establish sufficient condit...

A convex approach is proposed to deal with switched discrete-time systems with time-varying delays. It uses a parameter dependent Lyapunov-Krasovskii functional that allows to assure the robust stability or the robust stabilization of a switched system for arbitrary switching functions. The analysis and the design conditions are formulated as simple feasibility tests of linear matrix inequaliti...

In this paper, the problem of stability criteria for Markovian jumping BAM neural networks with leakage and discrete delays has been investigated. Some new sufficient condition are derived based on a novel Lyapunov-Krasovskii functional approach. These new criteria based on delay partitioning idea are proved to be less conservative because free-weighting matrices method and a convex optimizatio...

Abstract: In this paper, we consider the problem of dissipativity and passivity analysis for complex-valued discrete-time neural networks with time-varying delays. The neural network under consideration is subject to time-varying. 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 ...

Based on Lyapunov-Krasovskii functional, this paper concerns an observerbased stabilization problem for linear time-delay systems with delayed state and input. If the time-delay constants are both available for the li.near time-delay system, an observerbased controller, in which the influence of the time-delays is considered, is given. And the design of the controller and observer satisfies the...

This note concerns the delay-dependent robust stability analysis for uncertain singular time-delay systems. The parameter uncertainty is assumed to be norm-bounded and possibly time-varying, while the time delay considered here is assumed to be constant but unknown. By using a new Lyapunov-krasovskii functional which splits the whole delay interval into two subintervals and defines a different ...

This paper addresses the problem of stability analysis for a class of genetic regulatory networks (GRNs) with Markovian jumping parameters and time-varying delays. By constructing a novel Lyapunov-Krasovskii functional (LKF) and using an appropriate enlargement scheme, new stability criteria are proposed in terms of linear matrix inequalities, which can guarantee the mean square stability of Ma...

The problem of robust control for uncertain discrete-time Takagi and Sugeno (T-S) fuzzy networked control systems (NCSs) is investigated in this paper subject to state quantization. By taking into consideration network induced delays and packet dropouts, an improved model of network-based control is developed. A less conservative delay-dependent stability condition for the closed NCSs is derive...

The stability for the switched Cohen-Grossberg neural networks with mixed time delays and αinverse Hölder activation functions is investigated under the switching rule with the average dwell time property. By applying multiple Lyapunov-Krasovskii functional approach and linear matrix inequality LMI technique, a delay-dependent sufficient criterion is achieved to ensure such switched neural netw...

The paper is engaged with the framework of designing adaptive fault estimation for linear continuous-time systems with distributed time delay. The Lyapunov-Krasovskii functional principle is enforced by imposing the integral partitioning method and a new equivalent delaydependent design condition for observer-based assessment of faults are established in terms of linear matrix inequalities. Asy...