Synchronization of Delayed Inertial Cohen–Grossberg Neural Networks Under Adaptive Feedback Controller

DOI

10.2991/ijcis.d.200402.001How to use a DOI?

Keywords

CGNNs; Adaptive synchronization; Inertial term; Time-varying delay

Abstract

This paper investigates the issue on adaptive synchronization of delayed inertial Cohen–Grossberg neural networks (ICGNNs). By adopting the method of variable transformation, the addressed model, which includes the so-called inertial term, is transformed into first-order differential equations. On the basis of the well-known invariant principle of functional differential equations, a novel and analytic scheme which ensures the adaptive synchronization between the drive-response system is proposed in component form. It is worth mentioning that we only need to impose one controller to the spilt systems to realize the adaptive synchronization, which is of less conservatism. At the end of this paper, a numerical example is provided to verify the feasibility of the derived theoretical results. The established figures validate that the numerical simulations coincide well with the developed theoretical results.

Copyright

© 2020 The Authors. Published by Atlantis Press SARL.

Open Access

This is an open access article distributed under the CC BY-NC 4.0 license (http://creativecommons.org/licenses/by-nc/4.0/).

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TY  - JOUR
AU  - Qun Huang
AU  - Jinde Cao
AU  - Qingshan Liu
PY  - 2020
DA  - 2020/04/17
TI  - Synchronization of Delayed Inertial Cohen–Grossberg Neural Networks Under Adaptive Feedback Controller
JO  - International Journal of Computational Intelligence Systems
SP  - 472
EP  - 478
VL  - 13
IS  - 1
SN  - 1875-6883
UR  - https://doi.org/10.2991/ijcis.d.200402.001
DO  - 10.2991/ijcis.d.200402.001
ID  - Huang2020
ER  -