文献类型：期刊文献

英文题名：Bipartite Synchronization of Multiple Memristor-Based Neural Networks With Antagonistic Interactions

作者：Li, Ning[1,2];Zheng, Wei Xing[2]

第一作者：李宁;Li, Ning

通讯作者：Zheng, WX[1]

机构：[1]Henan Univ Econ & Law, Coll Math & Informat Sci, Zhengzhou 450046, Peoples R China;[2]Western Sydney Univ, Sch Comp Data & Math Sci, Sydney, NSW 2751, Australia

第一机构：河南财经政法大学数学与信息科学学院

通讯机构：[1]corresponding author), Western Sydney Univ, Sch Comp Data & Math Sci, Sydney, NSW 2751, Australia.

年份：2021

卷号：32

期号：4

起止页码：1642-1653

外文期刊名：IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS

收录：;EI(收录号：20201808602783);Scopus(收录号：2-s2.0-85084060369);WOS:【SCI-EXPANDED(收录号:WOS:000637534200019)】；

基金：This work was supported in part by the National Natural Science Foundation of China under Grant 61603125 and Grant 11872175, in part by the Australian Research Council under Grant DP120104986, in part by the Chinese Scholarship Council under Grant 201708410029, in part by the NG Teng Fong/Sino Outstanding Youth Fund of HUEL under Grant hncjzfdxxhhtf201913, in part by the Scientific and Technological Innovative Talents of Henan Province under Grant 20IRTSTHN025, and in part by the NSW Cyber Security Network in Australia under Grant P00025091.

语种：英文

外文关键词：Synchronization; Couplings; Neural networks; Adaptation models; Adaptive control; Mathematical model; Adaptive control; bipartite synchronization; memristive neural networks; signed graph

摘要：In this article, by introducing a signed graph to describe the coopetition interactions among network nodes, the mathematical model of multiple memristor-based neural networks (MMNNs) with antagonistic interactions is established. Since the cooperative and competitive interactions coexist, the states of MMNNs cannot reach complete synchronization. Instead, they will reach the bipartite synchronization: all nodes' states will reach an identical absolute value but opposite sign. To reach bipartite synchronization, two kinds of the novel node- and edge-based adaptive strategies are proposed, respectively. First, based on the global information of the network nodes, a node-based adaptive control strategy is constructed to solve the bipartite synchronization problem of MMNNs. Secondly, a local edge-based adaptive algorithm is proposed, where the weight values of edges between two nodes will change according to the designed adaptive law. Finally, two simulation examples validate the effectiveness of the proposed adaptive controllers and bipartite synchronization criteria.