Abstract
This work delves into the passivity of fractional generalized Cohen–Grossberg neural networks (CGNNs) with proportional delays. In particular, two forms of Lipschitz conditions for activation function are considered. Some passivity criteria are given by utilizing the Schur Complement lemma, Lyapunov–Krasovskii functional approach and Cauchy matrix inequality. The presented conditions are derived as matrix inequality forms and related to the proportional factor and order. This can clearly reflect the influence of the order and proportional factor on the input–output energy of the system. Two examples are particularized to better substantiate the obtained passivity results.
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 callMore From: Communications in Nonlinear Science and Numerical Simulation
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.
