Global Robust Stability of Switched Interval Neural Networks with Discrete and Distributed Time-Varying Delays of Neural Type release_7meht7rozzgevfix6nndw677sq

by Huaiqin Wu, Ning Li, Kewang Wang, Guohua Xu, Qiangqiang Guo

Published in Mathematical Problems in Engineering by Hindawi Limited.

2012   Volume 2012, p1-18

Abstract

By combing the theories of the switched systems and the interval neural networks, the mathematics model of the switched interval neural networks with discrete and distributed time-varying delays of neural type is presented. A set of the interval parameter uncertainty neural networks with discrete and distributed time-varying delays of neural type are used as the individual subsystem, and an arbitrary switching rule is assumed to coordinate the switching between these networks. By applying the augmented Lyapunov-Krasovskii functional approach and linear matrix inequality (LMI) techniques, a delay-dependent criterion is achieved to ensure to such switched interval neural networks to be globally asymptotically robustly stable in terms of LMIs. The unknown gain matrix is determined by solving this delay-dependent LMIs. Finally, an illustrative example is given to demonstrate the validity of the theoretical results.
In application/xml+jats format

Archived Files and Locations

application/pdf  2.1 MB
file_y7kj7wn3d5hgfg6clinwnt6x7y
www.emis.de (web)
web.archive.org (webarchive)
application/pdf  2.1 MB
file_kk7l4bgburh6tponwsppfyx5oy
web.archive.org (webarchive)
downloads.hindawi.com (publisher)
Read Archived PDF
Preserved and Accessible
Type  article-journal
Stage   published
Year   2012
Language   en ?
Container Metadata
Open Access Publication
In DOAJ
In ISSN ROAD
In Keepers Registry
ISSN-L:  1024-123X
Work Entity
access all versions, variants, and formats of this works (eg, pre-prints)
Catalog Record
Revision: 1f59d7d5-9076-40e9-b330-9e3c55d580a6
API URL: JSON