Quasi-bipartite synchronization of signed delayed neural networks under impulsive effects

Guohong Mu; Lulu Li; Xiaodi Li

doi:10.1016/j.neunet.2020.05.012

Quasi-bipartite synchronization of signed delayed neural networks under impulsive effects

Neural Netw. 2020 Sep:129:31-42. doi: 10.1016/j.neunet.2020.05.012. Epub 2020 May 19.

Authors

Guohong Mu¹, Lulu Li², Xiaodi Li³

Affiliations

¹ School of Mathematics, Hefei University of Technology, Hefei, 230009, China. Electronic address: leopold_2015@163.com.
² School of Mathematics, Hefei University of Technology, Hefei, 230009, China. Electronic address: lululima@hfut.edu.cn.
³ School of Mathematics and Statistics, Shandong Normal University, Ji'nan 250014, China. Electronic address: lxd@sdnu.edu.cn.

PMID: 32485559
DOI: 10.1016/j.neunet.2020.05.012

Abstract

This paper mainly studies quasi-bipartite synchronization (QBPS) of signed delayed neural networks (SDNNs) under impulsive effects, in which the nodes have cooperative as well as antagonistic interactions. It is assumed that disturbance occurs in the communication channels between some neighboring agents at impulsive occurring instants. Under the balanced network topology, some sufficient criteria to achieve QBPS of SDNNs are proposed by utilizing algebraic graph theory and extended Halanay differential inequality. Moreover, for the QBPS error of SDNNs, the upper bound of the final error state is also provided explicitly. Two numerical examples are presented to demonstrate the correctness of the theoretical results.

Keywords: Delayed neural networks; Disturbance; Impulsive control; Quasi-bipartite synchronization.

MeSH terms

Communication
Neural Networks, Computer*
Time Factors