Abstract
In this paper, the global exponential stability is investigated for a class of neural networks with both discrete and distributed delays and norm-bounded uncertainties. The discrete delay considered in this paper is interval-like time-varying delay. By using Lyapunov stable theory and linear matrix inequality, the derived criteria are not only dependent on distributed delay but also on the lower bound and upper bound of discrete time delay. And we don’t need the restriction that the derivative of discrete time-varying delay is less than one. A numerical example is given to illustrate the effectiveness and improvement over some existing results.
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
