Open AccessFinite time Synchronization of Inertial Memristive Neural Networks with Time Varying Delay
Author(s) -
Yajing Pang,
Shengmei Dong
Publication year - 2021
Publication title -
international journal of computers, communications and control
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.422
H-Index - 33
eISSN - 1841-9844
pISSN - 1841-9836
DOI - 10.15837/ijccc.2021.3.4215
Subject(s) - synchronization (alternating current) , memristor , control theory (sociology) , inertial frame of reference , artificial neural network , computer science , lyapunov stability , lyapunov function , stability (learning theory) , control (management) , nonlinear system , channel (broadcasting) , physics , artificial intelligence , computer network , quantum mechanics , machine learning
Finite time synchronization control of inertial memristor-based neural networks with varying delay is considered. In view of drive and response concept, the sufficient conditions to ensure finite time synchronization issue of inertial memristive neural networks is given. Based on Lyapunov finite time asymptotic theory, a kind of feedback controllers is designed for inertial memristorbased neural networks to realize the finite time synchronization. Based on Lyapunov stability theory, close loop error system can be proved finite time and fixed time stable. Finally, illustrative example is given to illustrate the effectiveness of theoretical results.