Abstract
This paper investigates the global periodicity of neural networks with time-varying delays. Several conditions guaranteeing the existence, uniqueness, and global asymptotical and exponential stability of periodic solution are obtained. These criteria are expressed in terms of linear matrix inequalities, thus they can be efficiently verified. Moreover, according to the criteria, the maximal bound of time delays and the fastest convergence speed can also be estimated for the exponential periodicity of neural networks. Some examples are given to illustrate the effectiveness of the given criteria.
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
More From: IEEE Transactions on Circuits and Systems I: Regular Papers
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.