Quasi-Projective Synchronization of Distributed-Order Recurrent Neural Networks
Keyword(s):
In this paper, the quasi-projective synchronization of distributed-order recurrent neural networks is investigated. Firstly, based on the definition of the distributed-order derivative and metric space theory, two distributed-order differential inequalities are obtained. Then, by employing the Lyapunov method, Laplace transform, Laplace final value theorem, and some inequality techniques, the quasi-projective synchronization sufficient conditions for distributed-order recurrent neural networks are established in cases of feedback control and hybrid control schemes, respectively. Finally, two numerical examples are given to verify the effectiveness of the theoretical results.
2019 ◽
Vol 34
(03)
◽
pp. 2051005
◽
2020 ◽
Vol 15
(2)
◽
pp. 15
2018 ◽
Vol 2018
◽
pp. 1-11
◽
EXPONENTIAL STABILITY OF REACTION–DIFFUSION FUZZY RECURRENT NEURAL NETWORKS WITH TIME-VARYING DELAYS
2007 ◽
Vol 17
(09)
◽
pp. 3099-3108
◽
2014 ◽
Vol 25
(08)
◽
pp. 1450029
◽
2007 ◽
Vol 17
(03)
◽
pp. 207-218
◽