Dynamics analysis of fractional-order Hopfield neural networks

作     者：Iqbal M.Batiha Ramzi B.Albadarneh Shaher Momani Iqbal H.Jebril 

作者机构：Department of Mathematics International Center for Scientific Research and Studies(ICSRS)Jordan Department of MathematicsFaculty of Science The Hashemite UniversityZarqaJordan Department of Mathematics and Sciences College of Humanities and Sciences Ajman UniversityAjmanUAE Mathematics DepartmentAl Zaytoonah University of Jordan Queen Alia Airport St 594Amman 11733Jordan 

出 版 物：《International Journal of Biomathematics》 (生物数学学报（英文版）)

年 卷 期：2020年第13卷第8期

页      面：233-249页

核心收录：

学科分类：0711[理学-系统科学] 07[理学] 08[工学] 081101[工学-控制理论与控制工程] 0811[工学-控制科学与工程] 071102[理学-系统分析与集成] 081103[工学-系统工程] 

基　　金：supporting this work by the University Ajman Grant:2Q20-COVID-19-08 

主　　题：Fractional calculus fractional-order Hopfield neural network Predictor Corrector Adams Bashforth Moulton Method Benettin Wolf algorithm Lyapunov exponents 

摘      要：This paper proposes fractional-order systems for Hopfield Neural Network(HNN).The so-called Predictor Corrector Adams Bashforth Moulton Method(PCABMM)has been implemented for solving such *** comparisons between the PCABMM and the Runge-Kutla Method(RKM)solutions for the classical HNN reveal that the proposed technique is one of the powerful tools for handling these *** determine all Lyapunov exponents for them,the Benettin-Wolf algorithm has been involved in the *** on such algorithm,the Lyapunov exponents as a function of a given parameter and as another function of the fractional-order have been described,the intermittent chaos for these systems has been explored.A new result related to the Mittag-Leffler stability of some nonlinear Fractional-order Hopfield Neural Network(FoHNN)systems has been ***,the description and the dynamic analysis of those phenomena have been discussed and verified theoretically and numerically via illustrating the phase portraits and the Lyapunov exponents diagrams.