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research-article

Robustness analysis of uncertain dynamical neural networks with multiple time delays

Author:

Sibel SenanAuthors Info & Claims

Neural Networks, Volume 70, Issue C

Pages 53 - 60

https://doi.org/10.1016/j.neunet.2015.07.001

Published: 01 October 2015 Publication History

Abstract

This paper studies the problem of global robust asymptotic stability of the equilibrium point for the class of dynamical neural networks with multiple time delays with respect to the class of slope-bounded activation functions and in the presence of the uncertainties of system parameters of the considered neural network model. By using an appropriate Lyapunov functional and exploiting the properties of the homeomorphism mapping theorem, we derive a new sufficient condition for the existence, uniqueness and global robust asymptotic stability of the equilibrium point for the class of neural networks with multiple time delays. The obtained stability condition basically relies on testing some relationships imposed on the interconnection matrices of the neural system, which can be easily verified by using some certain properties of matrices. An instructive numerical example is also given to illustrate the applicability of our result and show the advantages of this new condition over the previously reported corresponding results.

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Cited By

Tan YWang XYang JHu J(2020)Robust Exponential Stability for Discrete-Time Quaternion-Valued Neural Networks with Time Delays and Parameter UncertaintiesNeural Processing Letters10.1007/s11063-020-10196-w51:3(2317-2335)Online publication date: 1-Jun-2020
https://dl.acm.org/doi/10.1007/s11063-020-10196-w
Yu YDong HWang ZLi J(2019)Delay-distribution-dependent non-fragile state estimation for discrete-time neural networks under event-triggered mechanismNeural Computing and Applications10.1007/s00521-018-3516-z31:11(7245-7256)Online publication date: 1-Nov-2019
https://dl.acm.org/doi/10.1007/s00521-018-3516-z
Syed Ali MGunasekaran NEsther Rani M(2017)Robust stability of hopfield delayed neural networks via an augmented L-K functionalNeurocomputing10.1016/j.neucom.2017.01.015234:C(198-204)Online publication date: 19-Apr-2017
https://dl.acm.org/doi/10.1016/j.neucom.2017.01.015
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Robustness analysis of uncertain dynamical neural networks with multiple time delays

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Published In

cover image Neural Networks

Neural Networks Volume 70, Issue C

October 2015

104 pages

ISSN:0893-6080

Issue’s Table of Contents

Copyright © Elsevier Ltd.

Publisher

Elsevier Science Ltd.

United Kingdom

Publication History

Published: 01 October 2015

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Cited By

Tan YWang XYang JHu J(2020)Robust Exponential Stability for Discrete-Time Quaternion-Valued Neural Networks with Time Delays and Parameter UncertaintiesNeural Processing Letters10.1007/s11063-020-10196-w51:3(2317-2335)Online publication date: 1-Jun-2020
https://dl.acm.org/doi/10.1007/s11063-020-10196-w
Yu YDong HWang ZLi J(2019)Delay-distribution-dependent non-fragile state estimation for discrete-time neural networks under event-triggered mechanismNeural Computing and Applications10.1007/s00521-018-3516-z31:11(7245-7256)Online publication date: 1-Nov-2019
https://dl.acm.org/doi/10.1007/s00521-018-3516-z
Syed Ali MGunasekaran NEsther Rani M(2017)Robust stability of hopfield delayed neural networks via an augmented L-K functionalNeurocomputing10.1016/j.neucom.2017.01.015234:C(198-204)Online publication date: 19-Apr-2017
https://dl.acm.org/doi/10.1016/j.neucom.2017.01.015
Lakshmanan SLim CPrakash MNahavandi SBalasubramaniam P(2017)Neutral-type of delayed inertial neural networks and their stability analysis using the LMI ApproachNeurocomputing10.1016/j.neucom.2016.12.020230:C(243-250)Online publication date: 22-Mar-2017
https://dl.acm.org/doi/10.1016/j.neucom.2016.12.020
Syed Ali MArik SEsther Rani M(2016)Passivity analysis of stochastic neural networks with leakage delay and Markovian jumping parametersNeurocomputing10.1016/j.neucom.2016.08.062218:C(139-145)Online publication date: 19-Dec-2016
https://dl.acm.org/doi/10.1016/j.neucom.2016.08.062
Yu YDong HWang ZRen WAlsaadi F(2016)Design of non-fragile state estimators for discrete time-delayed neural networks with parameter uncertaintiesNeurocomputing10.1016/j.neucom.2015.11.079182:C(18-24)Online publication date: 19-Mar-2016
https://dl.acm.org/doi/10.1016/j.neucom.2015.11.079
Bashir SQamar UKhan F(2016)IntelliHealthJournal of Biomedical Informatics10.1016/j.jbi.2015.12.00159:C(185-200)Online publication date: 1-Feb-2016
https://dl.acm.org/doi/10.1016/j.jbi.2015.12.001

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