Cluster synchronization of coupled complex-valued neural networks with leakage and time-varying delays in finite-time

AIMS Mathematics

article

N. Jayanthi¹  R. Santhakumari¹  Grienggrai Rajchakit³  Nattakan Boonsatit⁴  Anuwat Jirawattanapanit⁵ 

[1] Government Arts College;Sri Ramakrishna College of Arts and Science;Department of Mathematics, Faculty of Science, Maejo University;Faculty of Science and Technology, Rajamangala University of Technology Suvarnabhumi;Department of Mathematics, Faculty of Science, Phuket Rajabhat University

关键词: complex-valued neural networks;    leakage delay;    time-varying delay;    cluster synchronization;    finite-time synchronization;    Lyapunov stability theory;   

DOI  :  10.3934/math.2023104

学科分类：地球科学(综合)

来源: AIMS Press

【 摘 要 】

In cluster synchronization (CS), the constituents (i.e., multiple agents) are grouped into a number of clusters in accordance with a function of nodes pertaining to a network structure. By designing an appropriate algorithm, the cluster can be manipulated to attain synchronization with respect to a certain value or an isolated node. Moreover, the synchronization values among various clusters vary. The main aim of this study is to investigate the asymptotic and CS problem of coupled delayed complex-valued neural network (CCVNN) models along with leakage delay in finite-time (FT). In this paper, we describe several sufficient conditions for asymptotic synchronization by utilizing the Lyapunov theory for differential systems and the Filippov regularization framework for the realization of finite-time synchronization of CCVNNs with leakage delay. We also propose sufficient conditions for CS of the system under scrutiny. A synchronization algorithm is developed to indicate the usefulness of the theoretical results in case studies.

【 授权许可】

CC BY