Convergence analysis on inertial proportional delayed neural networks

Advances in Difference Equations

article

Zhang, Hong¹  Qian, Chaofan² 

[1] College of Mathematics and Physics, Hunan University of Arts and Science;School of Mathematics and Statistics, Changsha University of Science and Technology;Hunan Provincial Key Laboratory of Mathematical Modeling and Analysis in Engineering

关键词: Inertial neural networks;    Global convergence;    Proportional delay;    Non-reduced order strategy;   

DOI  :  10.1186/s13662-020-02737-3

学科分类：航空航天科学

来源: SpringerOpen

【 摘 要 】

This article mainly explores a class of inertial proportional delayed neural networks. Abstaining reduced order strategy, a novel approach involving differential inequality technique and Lyapunov function fashion is presented to open out that all solutions of the considered system with their derivatives are convergent to zero vector, which refines some previously known research. Moreover, an example and its numerical simulations are given to display the exactness of the proposed approach.

【 授权许可】

CC BY