Exponential stability of switched nonlinear time-varying systems with mixed delays: Comparison principle

2020 ◽  
Vol 357 (11) ◽  
pp. 6918-6931
Author(s):  
Yazhou Tian ◽  
Yuangong Sun
Keyword(s):  
Exponential Stability ◽  
Comparison Principle ◽  
Mixed Delays ◽  
Time Varying ◽  
Time Varying Systems

scholarly journals Existence and Global Exponential Stability of Almost Periodic Solutions for SICNNs with Nonlinear Behaved Functions and Mixed Delays

2010 ◽  
Vol 2010 ◽  
pp. 1-20 ◽  
Author(s):  
Xinsong Yang ◽  
Jinde Cao ◽  
Chuangxia Huang ◽  
Yao Long
Keyword(s):  
Exponential Stability ◽  
Periodic Solutions ◽  
Differential Inequality ◽  
Global Exponential Stability ◽  
Sufficient Conditions ◽  
Mixed Delays ◽  
Time Varying ◽  
Almost Periodic Solutions ◽  
Almost Periodic ◽  
Inequality Techniques

By using the Leray-Schauder fixed point theorem and differential inequality techniques, several new sufficient conditions are obtained for the existence and global exponential stability of almost periodic solutions for shunting inhibitory cellular neural networks with discrete and distributed delays. The model in this paper possesses two characters: nonlinear behaved functions and all coefficients are time varying. Hence, our model is general and applicable to many known models. Moreover, our main results are also general and can be easily deduced to many simple cases, including some existing results. An example and its simulation are employed to illustrate our feasible results.

scholarly journals Pth Moment Exponential Stability of Impulsive Stochastic Neural Networks with Mixed Delays

2012 ◽  
Vol 2012 ◽  
pp. 1-20 ◽  
Author(s):  
Xiaoai Li ◽  
Jiezhong Zou ◽  
Enwen Zhu
Keyword(s):  
Neural Networks ◽  
Exponential Stability ◽  
Stochastic Analysis ◽  
Differential Inequality ◽  
Stochastic Neural Networks ◽  
Mixed Delays ◽  
Time Varying ◽  
Inequality Technique ◽  
Pth Moment Exponential Stability ◽  
Moment Exponential Stability

This paper investigates the problem ofpth moment exponential stability for a class of stochastic neural networks with time-varying delays and distributed delays under nonlinear impulsive perturbations. By means of Lyapunov functionals, stochastic analysis and differential inequality technique, criteria onpth moment exponential stability of this model are derived. The results of this paper are completely new and complement and improve some of the previously known results (Stamova and Ilarionov (2010), Zhang et al. (2005), Li (2010), Ahmed and Stamova (2008), Huang et al. (2008), Huang et al. (2008), and Stamova (2009)). An example is employed to illustrate our feasible results.

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