title: Almost periodic solutions for a memristor-based neural networks with leakage, time-varying and distributed delays.
abstract: In this paper, we study the existence and global exponential stability of almost periodic solution for memristor-based neural networks with leakage, time-varying and distributed delays. Using a new Lyapunov function method, we prove that this delayed neural network has a unique almost periodic solution, which is globally exponentially stable. Moreover, the obtained conclusion on the almost periodic solution is applied to prove the existence and stability of periodic solution (or equilibrium point) for this delayed neural network with periodic coefficients (or constant coefficients).
authors.affiliation: School of Automation, Huazhong University of Science and Technology, Wuhan 430074, China; School of Computer Science and Technology, Hubei PolyTechnic University, Huangshi 435003, China. Electronic address: jiangping20140209@gmail.com.
authors.forename: Ping
authors.initials: P
authors.lastname: Jiang
authors.affiliation: School of Automation, Huazhong University of Science and Technology, Wuhan 430074, China; Key Laboratory of Image Processing and Intelligent Control of Education Ministry of China, Wuhan 430074, China. Electronic address: hustzgzeng@gmail.com.
authors.forename: Zhigang
authors.initials: Z
authors.lastname: Zeng
authors.affiliation: School of Automation, Huazhong University of Science and Technology, Wuhan 430074, China; Key Laboratory of Image Processing and Intelligent Control of Education Ministry of China, Wuhan 430074, China.
authors.forename: Jiejie
authors.initials: J
authors.lastname: Chen
mesh_terms: D006801:Humans; D016571:Neural Networks, Computer; D010507:Periodicity; D013997:Time Factors
keywords: Almost periodic solution; Global exponential stability; Leakage; Memristor-based neural networks; Time-varying and distributed delays