Stability Analysis of Neural Networks With Time-Varying Delay by Constructing Novel Lyapunov Functionals

Stability Analysis of Neural Networks With Time-Varying Delay by Constructing Novel Lyapunov Functionals

This paper presents two novel Lyapunov functionals for analyzing the stability of neural networks with time-varying delay. Based on our newly proposed Lyapunov functionals and a relaxed Wirtinger-based integral inequality, new stability criteria are derived in the form of linear matrix inequalities....

Ausführliche Beschreibung

Gespeichert in:
Bibliographische Detailangaben
Veröffentlicht in:IEEE transaction on neural networks and learning systems 2018-09, Vol.29 (9), p.4238-4247
Hauptverfasser: Lee, Tae H., Trinh, Hieu M., Park, Ju H.
Format: Artikel
Sprache:eng
Schlagworte:
Biological neural networks
Computer applications
Delay
Delay effects
Delays
Functionals
Linear matrix inequalities
Lyapunov functionals
Mathematical analysis
Matrix methods
Neural networks
Neurons
stability
Stability analysis
Stability criteria
Symmetric matrices
time-varying delay
Online-Zugang:Volltext bestellen
Tags: Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
Beschreibung
Zusammenfassung:This paper presents two novel Lyapunov functionals for analyzing the stability of neural networks with time-varying delay. Based on our newly proposed Lyapunov functionals and a relaxed Wirtinger-based integral inequality, new stability criteria are derived in the form of linear matrix inequalities. A comprehensive comparison of results is given to illustrate the newly proposed stability criteria from both the conservative and computational complexity point of views.
ISSN:2162-237X
2162-2388
DOI:10.1109/TNNLS.2017.2760979