title: Exponential stabilization and synchronization for fuzzy model of memristive neural networks by periodically intermittent control.
abstract: The problem of exponential stabilization and synchronization for fuzzy model of memristive neural networks (MNNs) is investigated by using periodically intermittent control in this paper. Based on the knowledge of memristor and recurrent neural network, the model of MNNs is formulated. Some novel and useful stabilization criteria and synchronization conditions are then derived by using the Lyapunov functional and differential inequality techniques. It is worth noting that the methods used in this paper are also applied to fuzzy model for complex networks and general neural networks. Numerical simulations are also provided to verify the effectiveness of theoretical results.
authors.affiliation: College of Electronic and Information Engineering, Southwest University, Chongqing 400715, China.
authors.forename: Shiju
authors.initials: S
authors.lastname: Yang
authors.affiliation: College of Electronic and Information Engineering, Southwest University, Chongqing 400715, China. Electronic address: cdli@swu.edu.cn.
authors.forename: Chuandong
authors.initials: C
authors.lastname: Li
authors.affiliation: Department of Mathematics, Texas A&M University at Qatar, Doha 23874, Qatar.
authors.forename: Tingwen
authors.initials: T
authors.lastname: Huang
mesh_terms: D000465:Algorithms; D017143:Fuzzy Logic; D019359:Knowledge; D008962:Models, Theoretical; D016571:Neural Networks, Computer; D017711:Nonlinear Dynamics
keywords: Exponential stabilization; Fuzzy model of memristive neural networks (MNNs); Intermittent control; Synchronization