Abstract
By constructing a suitable Lyapunov functional and using some inequalities, we investigate the existence, uniqueness and global exponential stability of periodic solutions for a class of generalized cellular neural networks with impulses and time-varying delays. Finally, an illustrative example and simulations are given to show the effectiveness of the main results.
Highlights
The dynamics of cellular neural networks has been deeply investigated due to its applicability in solving image processing, signal processing and pattern recognition problems [, ]
In practice, impulsive effects are inevitably encountered in implementation of networks, which can be found in information science, electronics, automatic control systems and so on
It is necessary to study the impulsive case of system ( )
Summary
The dynamics of cellular neural networks has been deeply investigated due to its applicability in solving image processing, signal processing and pattern recognition problems [ , ]. The study of the existence and exponential stability of periodic solutions for neural networks has received much attention and many known results have been obtained [ – ]. × fl xl t – σijl(t) + Ii(t), ( ). When τij(t) = τij, σijl(t) = σijl are constants, a set of verifiable sufficient conditions guaranteeing the existence and globally exponential stability of one periodic solution was derived. In this paper, by employing some inequalities and constructing a suitable Lyapunov functional, we aim to investigate the existence and exponential stability of a periodic solution for a class of nonautonomous neural networks with impulses and time-varying delays as follows: By appropriately choosing coefficients, system ( ) contains many models as its special cases, which were studied in [ , , , , , ] respectively
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Free) 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a call
