Open AccessSynchronization control of quaternion-valued memristive neural networks with and without event-triggered scheme
Author(s) -
Ruoyu Wei,
Jinde Cao
Publication year - 2019
Publication title -
cognitive neurodynamics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.83
H-Index - 41
eISSN - 1871-4099
pISSN - 1871-4080
DOI - 10.1007/s11571-019-09545-w
Subject(s) - quaternion , computer science , synchronization (alternating current) , correctness , controller (irrigation) , artificial neural network , control theory (sociology) , zeno's paradoxes , scheme (mathematics) , event (particle physics) , control (management) , artificial intelligence , algorithm , mathematics , telecommunications , mathematical analysis , channel (broadcasting) , physics , geometry , quantum mechanics , agronomy , biology
In this paper, the real-valued memristive neural networks (MNNs) are extended to quaternion field, a new class of neural networks named quaternion-valued memristive neural networks (QVMNNs) is then established. The problem of master-slave synchronization of this type of networks is investigated in this paper. Two types of controllers are designed: the traditional feedback controller and the event-triggered controller. Corresponding synchronization criteria are then derived based on Lyapunov method. Moreover, it is demonstrated that Zeno behavior can be avoided in case of the event-triggered strategy proposed in this work. Finally, corresponding simulation examples are proposed to demonstrate the correctness of the proposed results derived in this work.