Invariant set and attractor of discrete-time impulsive recurrent neural networks

Authors:
Bing Li;Qiankun Song
Affiliations:
Department of Mathematics, Chongqing Jiaotong University, Chongqing, China;Department of Mathematics, Chongqing Jiaotong University, Chongqing, China
Venue:
ISNN'11 Proceedings of the 8th international conference on Advances in neural networks - Volume Part I
Year:
2011

Citing 8
Cited 0

Matrix analysis

Matrix analysis
Asymptotic behavior of discrete solutions to delayed neural networks with impulses

Neurocomputing
Positive invariant and global exponential attractive sets of neural networks with time-varying delays

Neurocomputing
Invariant and attracting sets of impulsive delay difference equations with continuous variables

Computers & Mathematics with Applications
Improved delay-dependent exponential stability criteria for discrete-time recurrent neural networks with time-varying delays

Neurocomputing
A new approach to stability analysis of discrete-time recurrent neural networks with time-varying delay

Neurocomputing
New results on robust exponential stability for discrete recurrent neural networks with time-varying delays

Neurocomputing
Letters: New delay-dependent stability results for discrete-time recurrent neural networks with time-varying delay

Neurocomputing

Quantified Score

Hi-index	0.00

Visualization

Abstract

In this paper, we study the invariant set and attractor of the discrete-time impulsive recurrent neural networks (DIRNNs). By using a powerful delay difference inequality and properties of nonnegative matrices, we get some sufficient criteria to determine the invariant set and attractor of DIRNNs. Some examples demonstrate the efficiency.