Abstract
This work is devoted to the problem of H <inf xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">∞</inf> state estimation for memristor-based neural networks with unbounded time-varying delays. The solution-based estimation method is proposed in this paper to obtain the criteria to ensure that the augmented system consisting of the dynamic equations of the memristor-based neural networks and the observer error system is globally exponentially stable with H <inf xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">∞</inf> performance level. This approach requires neither model transformation nor construction of Lyapunov–Krasovskii functionals. Finally, one numerical example and its numerical simulations are used to illustrate the applicability 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
Disclaimer: 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.