2014
DOI: 10.4304/jcp.9.8.1834-1842
|View full text |Cite
|
Sign up to set email alerts
|

Dynamics in a Coupled FHN Model with Two Different Delays

Abstract: In this paper, a coupled FHN model with two different delays is investigated. The local stability and the existence of Hopf bifurcation for the system are analyzed. The effect of two different delays on dynamical behavior is discussed. Simulation results are presented to support theoretical analysis. Finally, main conclusions are included.

Help me understand this report

Search citation statements

Order By: Relevance

Paper Sections

Select...
2

Citation Types

0
2
0

Year Published

2015
2015
2016
2016

Publication Types

Select...
1
1

Relationship

0
2

Authors

Journals

citations
Cited by 2 publications
(2 citation statements)
references
References 23 publications
0
2
0
Order By: Relevance
“…The Fold-Hopf bifurcation is investigated in a coupled FHN neural system with delay by Zhen and Xu [49]. Fan and Hong [14] considered the stability and Hopf bifurcation of double delay coupled FHN neurons, see also [46]. The steady state bifurcations of two coupled FHN neurons due to coupling strength and small time delay is investigated in [50] and [36].…”
Section: Introductionmentioning
confidence: 99%
“…The Fold-Hopf bifurcation is investigated in a coupled FHN neural system with delay by Zhen and Xu [49]. Fan and Hong [14] considered the stability and Hopf bifurcation of double delay coupled FHN neurons, see also [46]. The steady state bifurcations of two coupled FHN neurons due to coupling strength and small time delay is investigated in [50] and [36].…”
Section: Introductionmentioning
confidence: 99%
“…However, only codimension-1 bifurcations are discussed in these papers. Fan and Hong [36], and also Xu et al [37], considered the stability and Hopf bifurcation of double delay coupled FHN system with different coupling strength. Yao and Tu [38] discussed the combined effect of coupling strength and multiple delays on the stability of the rest point, and they obtained stability switches in the coupled FHN neural system with multiple delays.…”
Section: Introductionmentioning
confidence: 99%