Abstract

The problem of global robust stability for neural networks with neutral-type time-varying delays is investigated in this paper. Neutral differential equations are used to construct this class of neural networks. The time-varying delay function is bounded, and it is not required to be continuously differentiable. A new delay-dependent global stability criterion is derived based on the Lyapunov-Krasovskii functional approach. The criterion is formulated in terms of a linear matrix inequality. Numerical examples are given to illustrate the validity of the proposed stability criterion.

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 call

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.