Improved delay-dependent globally asymptotic stability of delayed uncertain recurrent neural networks with Markovian jumping parameters

In this paper, we have improved delay-dependent stability criteria for recurrent neural networks with a delay varying over a range and Markovian jumping parameters. The criteria improve over some previous ones in that they have fewer matrix variables yet less conservatism. In addition, a numerical e...

Full description

Saved in:
Bibliographic Details
Published in:Chinese physics B 2010-06, Vol.19 (6), p.154-161, Article 060512
Main Author: 籍艳 崔宝同
Format: Article
Language:English
Subjects:
Asymptotic properties
Criteria
Jumping
Mathematical analysis
Mathematical models
Matlab
Recurrent neural networks
Stability
Citations: Items that this one cites
Items that cite this one
Online Access:Get full text
Tags: Add Tag
No Tags, Be the first to tag this record!
Description
Summary:In this paper, we have improved delay-dependent stability criteria for recurrent neural networks with a delay varying over a range and Markovian jumping parameters. The criteria improve over some previous ones in that they have fewer matrix variables yet less conservatism. In addition, a numerical example is provided to illustrate the applicability of the result using the linear matrix inequality toolbox in MATLAB.
ISSN:1674-1056
2058-3834
DOI:10.1088/1674-1056/19/6/060512