Abstract
In this paper, the stability is discussed for high-order neural networks with proportional delay. The proportional delay is a time-varying unbounded delay and different from the constant delay, bounded time-varying delays and distributed delays. Based on Lyapunov method, matrix measure and generalized Halanay inequality, a criterion is obtained to ensure the pth exponential stability of high-order neural networks with proportional delay. The result can be extended to the neural networks with proportional delay or multiple proportional delays. The obtained results are simple, effective and easy to be verified. The simulating examples are exploited to illustrate the improvement and advantages of the obtained results in comparison with some existing 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.