| Updated in 8/31/2017 4:04:26 PM |
Viewed: 434 times |
(Journal Article) |
Neural networks : the official journal of the International Neural Network Society 61: 68-74 (2015)
Dynamic analysis of periodic solution for high-order discrete-time Cohen-Grossberg neural networks with time delays.
Kaiyun Sun
,
Ancai Zhang
,
Jianlong Qiu
,
Xiangyong Chen
,
Chengdong Yang
,
Xiao Chen
ABSTRACT
In this paper, we analyze the dynamic behavior of periodic solution for the high-order discrete-time Cohen-Grossberg neural networks (CGNNs) with time delays. First, the existence is studied based on the continuation theorem of coincidence degree theory and Young's inequality. And then, the criterion for the global exponential stability is given using Lyapunov method. Finally, simulation result shows the effectiveness of our proposed criterion.