Add to ORKGThe problem of global robust stability of neural networks with time delays and uncertainties is investigated. The uncertainties are assumed to be norm-bounded. The problem is discussed based on the Lyapunov method and linear matrix inequality (LMI) techniques. A novel criterion is given to ascertain the robust stability of the system. The criterion is expressed in terms of LMIs. It is computationally efficient, since the LMIs can be easily solvable by various convex optimization algorithms
In this paper, we investigate the robust stability problem for the class of delayed neural networks ...
This paper investigates the global robust convergence properties of continuous-time neural networks ...
This paper investigates the robust stability problem for dynamical neural networks in the presence o...
AbstractIn this paper, we study the global robust stability of neural networks with time varying del...
This paper studies the problem of robust stability of dynamical neural networks with discrete time d...
Abstract: An improved robust global stability criterion is developed for uncertain neural networks w...
In this paper, we study the global asymptotic robust stability of delayed neural networks with norm-...
This paper deals with the problem of robust stability for uncertain neural networks with time-varyin...
This paper studies the problem of establishing robust asymptotic stability of neural networks with m...
Global robust convergence properties of continuous-time neural networks with discrete delays are stu...
This paper is concerned with the global asymptotic stability problem of dynamical neural networks wi...
This Letter is concerned with the problem of robust stability analysis for interval neural networks ...
In this paper, by using Lyapunov stability theorems, we present a new sufficient condition for the e...
In this paper, we continue to explore application of nonsmooth analysis to the study of global asymp...
Global robust convergence properties of continuous-time neural networks with discrete delays are stu...
In this paper, we investigate the robust stability problem for the class of delayed neural networks ...
This paper investigates the global robust convergence properties of continuous-time neural networks ...
This paper investigates the robust stability problem for dynamical neural networks in the presence o...
AbstractIn this paper, we study the global robust stability of neural networks with time varying del...
This paper studies the problem of robust stability of dynamical neural networks with discrete time d...
Abstract: An improved robust global stability criterion is developed for uncertain neural networks w...
In this paper, we study the global asymptotic robust stability of delayed neural networks with norm-...
This paper deals with the problem of robust stability for uncertain neural networks with time-varyin...
This paper studies the problem of establishing robust asymptotic stability of neural networks with m...
Global robust convergence properties of continuous-time neural networks with discrete delays are stu...
This paper is concerned with the global asymptotic stability problem of dynamical neural networks wi...
This Letter is concerned with the problem of robust stability analysis for interval neural networks ...
In this paper, by using Lyapunov stability theorems, we present a new sufficient condition for the e...
In this paper, we continue to explore application of nonsmooth analysis to the study of global asymp...
Global robust convergence properties of continuous-time neural networks with discrete delays are stu...
In this paper, we investigate the robust stability problem for the class of delayed neural networks ...
This paper investigates the global robust convergence properties of continuous-time neural networks ...
This paper investigates the robust stability problem for dynamical neural networks in the presence o...