title: Stability analysis of fractional-order Hopfield neural networks with time delays.
abstract: This paper investigates the stability for fractional-order Hopfield neural networks with time delays. Firstly, the fractional-order Hopfield neural networks with hub structure and time delays are studied. Some sufficient conditions for stability of the systems are obtained. Next, two fractional-order Hopfield neural networks with different ring structures and time delays are developed. By studying the developed neural networks, the corresponding sufficient conditions for stability of the systems are also derived. It is shown that the stability conditions are independent of time delays. Finally, numerical simulations are given to illustrate the effectiveness of the theoretical results obtained in this paper.
authors.affiliation: Department of Mathematics, Beijing Jiaotong University, Beijing, 100044, PR China. Electronic address: wanghu1985712@163.com.
authors.forename: Hu
authors.initials: H
authors.lastname: Wang
authors.affiliation: Department of Mathematics, Beijing Jiaotong University, Beijing, 100044, PR China. Electronic address: ygyu@bjtu.edu.cn.
authors.forename: Yongguang
authors.initials: Y
authors.lastname: Yu
authors.affiliation: Department of Mathematics, Beijing Jiaotong University, Beijing, 100044, PR China. Electronic address: guoguang.wen@bjtu.edu.cn.
authors.forename: Guoguang
authors.initials: G
authors.lastname: Wen
mesh_terms: D016014:Linear Models; D016571:Neural Networks, Computer; D013997:Time Factors
keywords: Fractional-order; Hopfield neural networks; Hub structure; Ring structure; Stability; Time delays