Abstract

This paper addresses the global exponential dissipativity (GED) of impulsive recurrent neural networks (IRNNs) with proportional delays. By introducing some adjustable parameters, skillfully designing several Lyapunov functionals and utilizing matrix norm properties, serval delay-dependent GED criteria are developed, and global attractive sets (GAS) and global exponential attractive sets (GEAS) of the proposed system are given. These adjustable parameters are related to the exponential decay rate and contribute greatly to expand the attractive sets of this paper. Here the criteria proposed improve and extend the earlier global dissipativity criteria. Several numerical examples are used to verify the obtained results and show that the obtained results are independent of each other.

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.