Open AccessFinite‐time synchronisation of neural networks with discrete and distributed delays via periodically intermittent memory feedback control
Author(s) -
Yang Fei,
Mei Jun,
Wu Zhou
Publication year - 2016
Publication title -
iet control theory and applications
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.059
H-Index - 108
eISSN - 1751-8652
pISSN - 1751-8644
DOI - 10.1049/iet-cta.2015.1326
Subject(s) - intermittent control , control theory (sociology) , artificial neural network , correctness , computer science , synchronization (alternating current) , discrete time and continuous time , chaotic , linear matrix inequality , control (management) , differential (mechanical device) , stability (learning theory) , mathematics , control engineering , algorithm , mathematical optimization , engineering , artificial intelligence , computer network , channel (broadcasting) , statistics , machine learning , aerospace engineering
In this study, finite‐time synchronisation between two chaotic systems with discrete and distributed delays is investigated by using periodically intermittent memory feedback control. Based on finite‐time stability theory, some novel and effective synchronisation criteria of intermittent control are derived by means of linear matrix inequalities and differential inequality techniques. Furthermore, a necessary condition of finite‐time synchronisation of intermittent control is given for neural networks with discrete and distributed delays. A numerical example on two chaotic neural networks shows the effectiveness and correctness of the derived theoretical results. In addition, a secure communication synchronisation problem is presented to demonstrate practical effectiveness of the proposed method.