Abstract
This paper studies the uniqueness and global exponential stability of the equilibrium point for memristor-based recurrent neural networks with time-varying delays. By employing Lyapunov functional and theory of differential equations with discontinuous right-hand side, we establish several sufficient conditions for exponential stability of the equilibrium point. In comparison with the existing results, the proposed stability conditions are milder and more general, and can be applied to the memristor-based neural networks model whose connection weight changes continuously. Numerical examples are also presented to show the effectiveness of the theoretical 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.
