Regular Papers

International Journal of Control, Automation and Systems 2017; 15(4): 1600-1610

Published online July 20, 2017

https://doi.org/10.1007/s12555-016-0285-2

© The International Journal of Control, Automation, and Systems

New stability analysis for generalized neural networks with interval time-varying delays

Yanmin Liu, Junkang Tian*, Zerong Ren

Zunyi Normal College

Abstract

This paper deals with the problem of delay-dependent stability for neural networks with interval timevarying delays. First, we divided delay interval into two parts. Second, a new Lyapunov-Krasovskii functional is constructed, and relationships between the augmented state vectors have been fully considered, which may yield less conservative results. Third, based on free-matrix-based integral inequality method and reciprocally convex technique, some new less conservative delay-dependent stability criteria have been obtained by combining with the new Lyapunov-Krasovskii functional. Finally, two numerical examples are given to show the effectiveness of the derived conditions over the existing ones."

Keywords Interval time-varying delay, linear matrix inequalities (LMIs), neural networks, stability analysis.

Article

Regular Papers

International Journal of Control, Automation and Systems 2017; 15(4): 1600-1610

Published online August 1, 2017 https://doi.org/10.1007/s12555-016-0285-2

Copyright © The International Journal of Control, Automation, and Systems.

New stability analysis for generalized neural networks with interval time-varying delays

Yanmin Liu, Junkang Tian*, Zerong Ren

Zunyi Normal College

Abstract

This paper deals with the problem of delay-dependent stability for neural networks with interval timevarying delays. First, we divided delay interval into two parts. Second, a new Lyapunov-Krasovskii functional is constructed, and relationships between the augmented state vectors have been fully considered, which may yield less conservative results. Third, based on free-matrix-based integral inequality method and reciprocally convex technique, some new less conservative delay-dependent stability criteria have been obtained by combining with the new Lyapunov-Krasovskii functional. Finally, two numerical examples are given to show the effectiveness of the derived conditions over the existing ones."

Keywords: Interval time-varying delay, linear matrix inequalities (LMIs), neural networks, stability analysis.

IJCAS
May 2024

Vol. 22, No. 5, pp. 1461~1759

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