Abstract
A class of discrete-time recurrent neural networks model is presented with the introduction of time-varying delays in the leakage terms and linear fractional uncertainties in parameters. The exponential stability analysis problem is studied, for the first time, for such kind of neural networks. In terms of linear matrix inequality approach, some delay-dependent stability criteria are established for the considered neural networks via a Lyapunov–Karasovskii functional. Three numerical examples are given 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 callMore From: IMA Journal of Mathematical Control and Information
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.
