Novel delay-dependent robust stability analysis for switched neutral-type neural networks with time-varying delays via SC technique

This paper studies a class of new neural networks referred to as switched neutral-type neural networks (SNTNNs) with time-varying delays, which combines switched systems with a class of neutral-type neural networks. The less conservative robust stability criteria for SNTNNs with time-varying delays...

Ausführliche Beschreibung

Bibliographische Detailangaben
Veröffentlicht in:IEEE transactions on systems, man, and cybernetics. Part B, Cybernetics : a publication of the IEEE Systems, Man, and Cybernetics Society. - 1996. - 40(2010), 6 vom: 15. Dez., Seite 1480-91
1. Verfasser: Zhang, Huaguang (VerfasserIn)
Weitere Verfasser: Liu, Zhenwei, Huang, Guang-Bin
Format: Online-Aufsatz
Sprache:English
Veröffentlicht: 2010
Zugriff auf das übergeordnete Werk:IEEE transactions on systems, man, and cybernetics. Part B, Cybernetics : a publication of the IEEE Systems, Man, and Cybernetics Society
Schlagworte:Journal Article Research Support, Non-U.S. Gov't
Beschreibung
Zusammenfassung:This paper studies a class of new neural networks referred to as switched neutral-type neural networks (SNTNNs) with time-varying delays, which combines switched systems with a class of neutral-type neural networks. The less conservative robust stability criteria for SNTNNs with time-varying delays are proposed by using a new Lyapunov-Krasovskii functional and a novel series compensation (SC) technique. Based on the new functional, SNTNNs with fast-varying neutral-type delay (the derivative of delay is more than one) is first considered. The benefit brought by employing the SC technique is that some useful negative definite elements can be included in stability criteria, which are generally ignored in the estimation of the upper bound of derivative of Lyapunov-Krasovskii functional in literature. Furthermore, the criteria proposed in this paper are also effective and less conservative in switched recurrent neural networks which can be considered as special cases of SNTNNs. The simulation results based on several numerical examples demonstrate the effectiveness of the proposed criteria
Beschreibung:Date Completed 30.03.2011
Date Revised 10.12.2019
published: Print-Electronic
Citation Status MEDLINE
ISSN:1941-0492
DOI:10.1109/TSMCB.2010.2040274