Exponential stabilization of memristor-based neural networks with unbounded time-varying delays  

作　　者：Jiemei ZHAO 

机构地区：[1]School of Mathematics and Computer Science,Wuhan Polytechnic University,Wuhan 430023,China

出　　处：《Science China(Information Sciences)》2021年第8期243-245,共3页中国科学（信息科学）（英文版）

基　　金：Research and Innovation Initiatives of WHPU(Grant No.2018Y20).

摘　　要：Dear editor,As a consequence of symmetry arguments,the memristor was predicted by Chua[1].As the fourth basic circuit element,its memory characteristic and nanometer dimensions are devoid of resistors,capacitors,and inductors.In the field of the dynamical behavior analysis for memristive neural networks(MNNs),information exchange and signal transmission among different neurons are time-varying activities and discrete time delays are frequently supposed to be bounded,which implies that the current state of a neuron depend only on a part of its history.

关 键 词：STABILIZATION DELAYS UNBOUNDED 

分 类 号：TN60[电子电信—电路与系统] TP183[自动化与计算机技术—控制理论与控制工程]