Zhang, Rui; Wang, Zhanshan; Jing, Yuanwei Exponential stability of a class of static neural networks with time varying delay. (Chinese. English summary) Zbl 1212.93244 J. Northeast. Univ., Nat. Sci. 30, No. 5, 613-616 (2009). Summary: Based on linear matrix inequalities and considering the different effects of change rate of time varying delay on the stability, two criteria for exponential stability are set up, i.e., a criterion that just depends on the upper bound of the delay and a criterion that depends wholly on the delay information. The two stability criteria obtained can be adapted to either a quickly changed or a slowly changed time varying delay, thus providing wider applications, less conservativeness and verification easy to do, and with some remarks given and in comparison to the results in earlier works, simulations are done to exemplify the effectiveness of the proposed approaches. MSC: 93D05 Lyapunov and other classical stabilities (Lagrange, Poisson, \(L^p, l^p\), etc.) in control theory 68T05 Learning and adaptive systems in artificial intelligence 92B20 Neural networks for/in biological studies, artificial life and related topics 93D20 Asymptotic stability in control theory Keywords:recurrent neural network; local field network; static neural network; Lyapunov function; global exponential stability; linear matrix inequality PDFBibTeX XMLCite \textit{R. Zhang} et al., J. Northeast. Univ., Nat. Sci. 30, No. 5, 613--616 (2009; Zbl 1212.93244)