This paper is concerned with the robust stability analysis problem for uncertain stochastic neural networks with interval time-varying delays. By utilizing a Lyapunov-Krasovskii functional and conducting stochastic analysis, the authors show that the addressed neural networks are globally, robustly, and asymptotically stable if a convex optimization problem is feasible. Some stability criteria ...

In this paper we introduce some stability criteria for impulsive fuzzy system of differential equations with finite delay in states. Firstly, a new comparison principle for fuzzy differential system compared to crisp ordinary differential equation, based on a notion of upper quasi-monotone nondecreasing, in N dimentional state space is presented. Furthermore, in order to analyze the stability o...

We present the clearance results of the HIRM+RIDE control configuration for the linear stability and handling criteria mostly used in the current industrial practice. The performed analysis is based on an optimisation-driven worst-case search. Two classes of linear stability related criteria are considered: the Nichols exclusion region based stability margin criterion and the unstable eigenvalu...

The existence of planets in stellar binary (and higher order) systems has now been confirmed by many observations. The stability of planetary orbits in these systems has been extensively studied, but no precise stability criteria have so far been introduced. Therefore, there is an urgent need for developing stringent mathematical criteria that allow us to precisely determine whether a planetary...

In this paper, we propose new sets of criteria for exponential robust stability of Takagi-Sugeno (T-S) fuzzy Hopfield neural networks. The L2−L∞ approach is applied to obtain new sets of stability criteria, under which T-S fuzzy Hopfield neural networks reduce the effect of external input to a prescribed level. These sets of criteria are presented based on the matrix norm and linear matrix ineq...

This paper is concerned with the stability and stabilization problems for discrete-time systems with interval time-varying delays. By construction of an augmented Lyapunov–Krasovskii functional and utilization of zero equalities, improved delay-dependent criteria for asymptotic stability of the systems are derived in terms of linear matrix inequalities (LMIs). Based on the proposed stability cr...

This paper presents several new robust stability conditions for linear discrete-time systems with polytopic parameter uncertainties and time-varying delay in the state. These stability criteria, derived by defining parameter-dependent Lyapunov functions, are not only dependent on the maximum and minimum delay bounds, but also dependent on uncertain parameters in the sense that different Lyapuno...

A cellular neural network (CNN) is a recurrent neural network model. Like other models of this kind, the complete stability issue remains an open question. Leaving aside the unstable cyclic output case, the existence of stable outputs itself, known as the partial stability problem, ends up being a quite reliable guarantee for complete stability. Yet, no necessary and sufficient condition for pa...