title: New passivity criteria for memristive uncertain neural networks with leakage and time-varying delays.
abstract: In this paper, the problem of passivity analysis is studied for memristor-based uncertain neural networks with leakage and time-varying delays. By combining differential inclusions with set-valued maps, the system of memristive neural networks is changed into the conventional one. By adding a triple quadratic integral and relaxing the requirement for the positive definiteness of some matrices, a proper Lyapunov-Krasovskii functional is constructed. Based on the establishment of the novel Lyapunov-Krasovskii functional, the new passivity criteria are derived by mainly applying Wirtinger-based double integral inequality, S-procedure and so on. Moreover, the conservatism of passivity conditions can be reduced. Finally, four numerical examples are given to show the effectiveness and less conservatism of the proposed criteria.
authors.affiliation: School of Mathematical Sciences, University of Electronic Science and Technology of China, Chengdu 611731, PR China; School of Sciences, Southwest Petroleum University, Chengdu 610050, PR China. Electronic address: shawion1980@yahoo.com.
authors.forename: Jianying
authors.initials: J
authors.lastname: Xiao
authors.affiliation: School of Mathematical Sciences, University of Electronic Science and Technology of China, Chengdu 611731, PR China.
authors.forename: Shouming
authors.initials: S
authors.lastname: Zhong
authors.affiliation: College of Chemistry and Chemical Engineering, Southwest Petroleum University, Chengdu 610050, PR China.
authors.forename: Yongtao
authors.initials: Y
authors.lastname: Li
mesh_terms: D000465:Algorithms; D003198:Computer Simulation; D016571:Neural Networks, Computer; D009474:Neurons; D035501:Uncertainty
keywords: Leakage delay; Lyapunov method; Memristive neural networks; Passivity; Time-varying delays; Uncertainty