Exponential H∞ synchronization and anti-synchronization of delayed discrete-time complex-valued neural networks with uncertainties

This paper investigates the problem of exponential synchronization and anti-synchronization for uncertain discrete-time neural networks (NNs) having time-varying delays with H∞ performance in complex domain. An output-feedback controller is utilized not only to guarantee the synchronization criteria...

Full description

Saved in:
Bibliographic Details
Published in:Mathematics and computers in simulation 2023-05, Vol.207, p.301-321
Main Authors: Priyanka, K. Sri Raja, Soundararajan, G., Kashkynbayev, Ardak, Nagamani, G.
Format: Article
Language:English
Subjects:
Anti-synchronization
Complex-valued neural networks
Linear matrix inequality
Lyapunov–Krasovskii functional
Output-feedback control
Synchronization
Citations: Items that this one cites
Items that cite this one
Online Access:Get full text
Tags: Add Tag
No Tags, Be the first to tag this record!
Description
Summary:This paper investigates the problem of exponential synchronization and anti-synchronization for uncertain discrete-time neural networks (NNs) having time-varying delays with H∞ performance in complex domain. An output-feedback controller is utilized not only to guarantee the synchronization criteria between the addressed discrete-time complex-valued neural networks (CVNNs) but also to reduce the effect of external disturbance. In order to assure the anti-synchronization criteria with H∞ performance for the proposed CVNNs, we have introduced the output-feedback controller by anti-synchronization error analysis. With the help of Lyapunov–Krasovskii functional (LKF), some linear matrix inequality (LMI) based sufficient conditions are derived for both synchronization and anti-synchronization criteria which can be validated through YALMIP toolbox in MATLAB software. At last, a numerical simulation result is provided to verify the correctness of the established theoretical results.
ISSN:0378-4754
1872-7166
DOI:10.1016/j.matcom.2023.01.002