Anti-periodic solutions for a class of Cohen–Grossberg neural networks with time-varying delays on time scales

2011 ◽  
Vol 42 (7) ◽  
pp. 1127-1132 ◽  
Author(s):  
Yongkun Li ◽  
Li Yang ◽  
Wanqin Wu
2015 ◽  
Vol 2015 ◽  
pp. 1-15 ◽  
Author(s):  
Yongkun Li ◽  
Lili Zhao ◽  
Li Yang

On a new type of almost periodic time scales, a class of BAM neural networks is considered. By employing a fixed point theorem and differential inequality techniques, some sufficient conditions ensuring the existence and global exponential stability ofC1-almost periodic solutions for this class of networks with time-varying delays are established. Two examples are given to show the effectiveness of the proposed method and results.


2014 ◽  
Vol 2014 ◽  
pp. 1-16 ◽  
Author(s):  
Yongkun Li ◽  
Lei Wang ◽  
Yu Fei

A class of shunting inhibitory cellular neural networks of neutral type with time-varying delays in the leakage term on time scales is proposed. Based on the exponential dichotomy of linear dynamic equations on time scales, fixed point theorems, and calculus on time scales we obtain some sufficient conditions for the existence and global exponential stability of periodic solutions for that class of neural networks. The results of this paper are completely new and complementary to the previously known results even if the time scale𝕋=ℝorℤ. Moreover, we present illustrative numerical examples to show the feasibility of our results.


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