Exponential Stability of Almost Periodic Solutions for Memristor-Based Neural Networks with Distributed Leakage Delays.
In this letter, we deal with a class of memristor-based neural networks with distributed leakage delays. By applying a new Lyapunov function method, we obtain some sufficient conditions that ensure the existence, uniqueness, and global exponential stability of almost periodic solutions of neural networks. We apply the results of this solution to prove the existence and stability of periodic solutions for this delayed neural network with periodic coefficients. We then provide an example to illustrate the effectiveness of the theoretical results. Our results are completely new and complement the previous studies Chen, Zeng, and Jiang ( 2014 ) and Jiang, Zeng, and Chen ( 2015 ).
Guizhou Key Laboratory of Economics System Simulation, Guizhou University of Finance and Economics, Guiyang 550004, P.R. China xcj403@126.com.
Changjin
C
Xu
School of Mathematics and Statistics, Henan University of Science and Technology, Luoyang 471023, P.R. China lpllpl_lpl@163.com.
Peiluan
P
Li
School of Mathematics and Statistics, Guizhou University of Finance and Economics Guiyang 550004, P.R. China ypanggy@outlook.com.
Yicheng
Y
Pang
D009415:Nerve Net; D013997:Time Factors