Passivity analysis of uncertain stochastic neural network with leakage and distributed delays under impulsive perturbations

Senthil Raj; Raja Ramachandran; Samidurai Rajendiran; Jinde Cao; Xiaodi Li

Kybernetika (2018)

  • Volume: 54, Issue: 1, page 3-29
  • ISSN: 0023-5954

Abstract

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In this paper, the problem of passivity analysis for a class of uncertain stochastic neural networks with mixed delays and impulsive control is investigated. The mixed delays include constant delay in the leakage term, discrete and distributed delays. The discrete delays are assumed to be time-varying and belong to a given interval, which means that the lower and upper bounds of interval time-varying delays are available. By using Lyapunov stability theory, stochastic analysis, linear matrix inequality techniques and introducing some free-weighting matrices, several novel sufficient conditions are derived to guarantee the passivity of the suggested system in the sense of mean square under two cases: with known or unknown parameters. It is believed that these results are significant and useful for the design and applications of impulsive stochastic neural networks. Finally, two numerical examples are provided to show the effectiveness of the theoretical results.

How to cite

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Raj, Senthil, et al. "Passivity analysis of uncertain stochastic neural network with leakage and distributed delays under impulsive perturbations." Kybernetika 54.1 (2018): 3-29. <http://eudml.org/doc/294305>.

@article{Raj2018,
abstract = {In this paper, the problem of passivity analysis for a class of uncertain stochastic neural networks with mixed delays and impulsive control is investigated. The mixed delays include constant delay in the leakage term, discrete and distributed delays. The discrete delays are assumed to be time-varying and belong to a given interval, which means that the lower and upper bounds of interval time-varying delays are available. By using Lyapunov stability theory, stochastic analysis, linear matrix inequality techniques and introducing some free-weighting matrices, several novel sufficient conditions are derived to guarantee the passivity of the suggested system in the sense of mean square under two cases: with known or unknown parameters. It is believed that these results are significant and useful for the design and applications of impulsive stochastic neural networks. Finally, two numerical examples are provided to show the effectiveness of the theoretical results.},
author = {Raj, Senthil, Ramachandran, Raja, Rajendiran, Samidurai, Cao, Jinde, Li, Xiaodi},
journal = {Kybernetika},
keywords = {distributed delays; leakage delay; passivity impulses; stochastic disturbances},
language = {eng},
number = {1},
pages = {3-29},
publisher = {Institute of Information Theory and Automation AS CR},
title = {Passivity analysis of uncertain stochastic neural network with leakage and distributed delays under impulsive perturbations},
url = {http://eudml.org/doc/294305},
volume = {54},
year = {2018},
}

TY - JOUR
AU - Raj, Senthil
AU - Ramachandran, Raja
AU - Rajendiran, Samidurai
AU - Cao, Jinde
AU - Li, Xiaodi
TI - Passivity analysis of uncertain stochastic neural network with leakage and distributed delays under impulsive perturbations
JO - Kybernetika
PY - 2018
PB - Institute of Information Theory and Automation AS CR
VL - 54
IS - 1
SP - 3
EP - 29
AB - In this paper, the problem of passivity analysis for a class of uncertain stochastic neural networks with mixed delays and impulsive control is investigated. The mixed delays include constant delay in the leakage term, discrete and distributed delays. The discrete delays are assumed to be time-varying and belong to a given interval, which means that the lower and upper bounds of interval time-varying delays are available. By using Lyapunov stability theory, stochastic analysis, linear matrix inequality techniques and introducing some free-weighting matrices, several novel sufficient conditions are derived to guarantee the passivity of the suggested system in the sense of mean square under two cases: with known or unknown parameters. It is believed that these results are significant and useful for the design and applications of impulsive stochastic neural networks. Finally, two numerical examples are provided to show the effectiveness of the theoretical results.
LA - eng
KW - distributed delays; leakage delay; passivity impulses; stochastic disturbances
UR - http://eudml.org/doc/294305
ER -

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