Abstract: This paper is concerned with the stability problem
with two additive time-varying delay components. By choosing one
augmented Lyapunov-Krasovskii functional, using some new zero
equalities, and combining linear matrix inequalities (LMI)
techniques, two new sufficient criteria ensuring the global stability
asymptotic stability of DNNs is obtained. These stability criteria are
present in terms of linear matrix inequalities and can be easily
checked. Finally, some examples are showed to demonstrate the
effectiveness and less conservatism of the proposed method.
Abstract: This paper deals with the problem of delay-dependent
stability for neural networks with distributed delays. Some new
sufficient condition are derived by constructing a novel
Lyapunov-Krasovskii functional approach. The criteria are
formulated in terms of a set of linear matrix inequalities, this is
convenient for numerically checking the system stability using the
powerful MATLAB LMI Toolbox. Moreover, in order to show the
stability condition in this paper gives much less conservative results
than those in the literature, numerical examples are considered.
Abstract: Utilizing the Lyapunov functional method and combining linear matrix inequality (LMI) techniques and integral inequality approach (IIA) to analyze the global asymptotic stability for delayed neural networks (DNNs),a new sufficient criterion ensuring the global stability of DNNs is obtained.The criteria are formulated in terms of a set of linear matrix inequalities,which can be checked efficiently by use of some standard numercial packages.In order to show the stability condition in this paper gives much less conservative results than those in the literature,numerical examples are considered.