Stability and bifurcation of a neuron model with delay-dependent parameters

被引：0
|
作者：
Xu, X [1 ]
Liang, YC
机构：
[1] Jilin Univ, Coll Math, Key Lab Symbol Computat & Knowledge Engn, Minist Educ, Changchun 130012, Peoples R China
[2] Nanjing Univ Aeronaut & Astronaut, Inst Vibrat Engn Res, Nanjing 210016, Peoples R China
[3] Jilin Univ, Coll Comp Sci & Technol, Key Lab Symbol Computat & Knowledge Engn, Minist Educ, Changchun 130012, Peoples R China
来源：
ADVANCES IN NEURAL NETWORKS - ISNN 2005, PT 1, PROCEEDINGS | 2005年 / 3496卷
关键词：
D O I：
暂无
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
An analytical method is proposed to study the dynamics of a neuron model with delay-dependent parameters. Stability and bifurcation of this model are analyzed using stability switches and Hopf bifurcation proposition. A series of critical time delay are determined and a simple stable criterion is given according to the range of parameters. Through the analysis for the bifurcation, it is shown that a very large delay could also stabilize the system. This conclusion is quite different from that of the system with only delay-independent parameters.
引用
收藏
页码：334 / 339
页数：6
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