Abstract
In this paper, we study finite-time synchronization of a memristive neural network (MNN) with impulsive effect and stochastic perturbation. Because the parameters of the MNN are state-dependent, the traditional analytical method and control technique can not be directly used. In previous research, differential inclusions theory and set-valued mappings technique have been recently introduced to deal with this MNN system. But, we study the synchronization of MNN without using the previous solution technique. A novel analytical technique is first proposed to transform the MNN to a class of neural network (cNN) with uncertain parameters. The finite-time synchronization is obtained by disposing of parameter mismatch, impulsive effect or stochastic perturbation for the cNN. Several useful criteria of synchronization are obtained based on Lyapunov function, linear matrix inequality (LMI) and finite-time stability theory. Finally, two examples are given to demonstrate the effectiveness of our proposed method.
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.