Stability of Markovian jump neural networks with mode-dependent delays and generally incomplete transition probability

Jing Xie; Yonggui Kao

doi:10.1007/s00521-014-1812-9

Stability of Markovian jump neural networks with mode-dependent delays and generally incomplete transition probability

Jing Xie
, Yonggui Kao^*

^*Corresponding author for this work

School of Science, Harbin Institute of Technology Weihai
Ocean University of China

Research output: Contribution to journal › Article › peer-review

8 Scopus citations

Abstract

This paper deals with the robust exponential stability problem for a class of Markovian jump neural networks with mode-dependent delays and generally incomplete transition probability. The delays vary randomly depending on the mode of the networks. Each transition rate can be completely unknown, or only its estimate value is known. By using a new Lyapunov–Krasovskii functional, a delay-dependent stability criterion is presented in terms of linear matrix inequalities (LMIs). The proposed LMI results extend the earlier publications. Finally, a numerical example is given to show the effectiveness and efficiency of the results.

Original language	English
Pages (from-to)	1537-1553
Number of pages	17
Journal	Neural Computing and Applications
Volume	26
Issue number	7
DOIs	https://doi.org/10.1007/s00521-014-1812-9
State	Published - 21 Oct 2015
Externally published	Yes

Keywords

Generally incomplete transition probability
Linear matrix inequality
Markovian jumping neural networks
Mode-dependent delay
Robust exponential stability

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10.1007/s00521-014-1812-9

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title = "Stability of Markovian jump neural networks with mode-dependent delays and generally incomplete transition probability",

abstract = "This paper deals with the robust exponential stability problem for a class of Markovian jump neural networks with mode-dependent delays and generally incomplete transition probability. The delays vary randomly depending on the mode of the networks. Each transition rate can be completely unknown, or only its estimate value is known. By using a new Lyapunov–Krasovskii functional, a delay-dependent stability criterion is presented in terms of linear matrix inequalities (LMIs). The proposed LMI results extend the earlier publications. Finally, a numerical example is given to show the effectiveness and efficiency of the results.",

keywords = "Generally incomplete transition probability, Linear matrix inequality, Markovian jumping neural networks, Mode-dependent delay, Robust exponential stability",

author = "Jing Xie and Yonggui Kao",

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T1 - Stability of Markovian jump neural networks with mode-dependent delays and generally incomplete transition probability

AU - Xie, Jing

AU - Kao, Yonggui

PY - 2015/10/21

Y1 - 2015/10/21

N2 - This paper deals with the robust exponential stability problem for a class of Markovian jump neural networks with mode-dependent delays and generally incomplete transition probability. The delays vary randomly depending on the mode of the networks. Each transition rate can be completely unknown, or only its estimate value is known. By using a new Lyapunov–Krasovskii functional, a delay-dependent stability criterion is presented in terms of linear matrix inequalities (LMIs). The proposed LMI results extend the earlier publications. Finally, a numerical example is given to show the effectiveness and efficiency of the results.

AB - This paper deals with the robust exponential stability problem for a class of Markovian jump neural networks with mode-dependent delays and generally incomplete transition probability. The delays vary randomly depending on the mode of the networks. Each transition rate can be completely unknown, or only its estimate value is known. By using a new Lyapunov–Krasovskii functional, a delay-dependent stability criterion is presented in terms of linear matrix inequalities (LMIs). The proposed LMI results extend the earlier publications. Finally, a numerical example is given to show the effectiveness and efficiency of the results.

KW - Generally incomplete transition probability

KW - Linear matrix inequality

KW - Markovian jumping neural networks

KW - Mode-dependent delay

KW - Robust exponential stability

UR - https://www.scopus.com/pages/publications/84939573971

U2 - 10.1007/s00521-014-1812-9

DO - 10.1007/s00521-014-1812-9

M3 - 文章

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VL - 26

SP - 1537

EP - 1553

JO - Neural Computing and Applications

JF - Neural Computing and Applications

IS - 7

ER -

Stability of Markovian jump neural networks with mode-dependent delays and generally incomplete transition probability

Abstract

Keywords

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