Abstract
In real nervous systems and in the implementation of very large-scale integration (VLSI) circuits, noise is unavoidable, which leads to the stochastic model of the memristor-based recurrent neural networks. Exponential stability of stochastic memristor-based recurrent neural networks with time-varying delays is studied and some sufficient conditions in terms of inequalities are derived. Numerical examples are given to demonstrate the effectiveness of the proposed stability criteria.
Sign-in/Register to access full text options 
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 callDisclaimer: 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.
