Finite-Time Nonfragile Dissipative Control for Discrete-Time Neural Networks with Markovian Jumps and Mixed Time-Delays

This paper considers the stochastic finite-time dissipative (SFTD) control problem based on nonfragile controller for discrete-time neural networks (NNS) with Markovian jumps and mixed delays, in which the mode switching phenomenon, is described as Markov chain, and the mixed delays are composed of...

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Main Authors: Ling Hou, Dongyan Chen, Chan He
Format: Article
Language:English
Published: Wiley 2019-01-01
Series:Complexity
Online Access:http://dx.doi.org/10.1155/2019/5748923
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author Ling Hou
Dongyan Chen
Chan He
author_facet Ling Hou
Dongyan Chen
Chan He
author_sort Ling Hou
collection DOAJ
description This paper considers the stochastic finite-time dissipative (SFTD) control problem based on nonfragile controller for discrete-time neural networks (NNS) with Markovian jumps and mixed delays, in which the mode switching phenomenon, is described as Markov chain, and the mixed delays are composed of discrete time-varying delay and distributed delays. First, by selecting an appropriate Lyapunov-Krasovskii functional and applying stochastic analysis methods, some parameters-dependent sufficient conditions for solvability of stochastic finite-time boundedness are derived. Then, the main results are extended to SFTD control. Furthermore, existence condition of nonfragile controller is derived based on solution of linear matrix inequalities (LMIs). Finally, two numerical examples are employed to show the effectiveness of the obtained methods.
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institution Kabale University
issn 1076-2787
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publishDate 2019-01-01
publisher Wiley
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series Complexity
spelling doaj-art-7996a72f2b454709a07d3ffc722be3c92025-02-03T01:22:30ZengWileyComplexity1076-27871099-05262019-01-01201910.1155/2019/57489235748923Finite-Time Nonfragile Dissipative Control for Discrete-Time Neural Networks with Markovian Jumps and Mixed Time-DelaysLing Hou0Dongyan Chen1Chan He2Department of Mathematics, Harbin University of Science and Technology, Harbin 150080, ChinaDepartment of Mathematics, Harbin University of Science and Technology, Harbin 150080, ChinaDepartment of Mathematics, North University of China, Taiyuan 030051, Shanxi, ChinaThis paper considers the stochastic finite-time dissipative (SFTD) control problem based on nonfragile controller for discrete-time neural networks (NNS) with Markovian jumps and mixed delays, in which the mode switching phenomenon, is described as Markov chain, and the mixed delays are composed of discrete time-varying delay and distributed delays. First, by selecting an appropriate Lyapunov-Krasovskii functional and applying stochastic analysis methods, some parameters-dependent sufficient conditions for solvability of stochastic finite-time boundedness are derived. Then, the main results are extended to SFTD control. Furthermore, existence condition of nonfragile controller is derived based on solution of linear matrix inequalities (LMIs). Finally, two numerical examples are employed to show the effectiveness of the obtained methods.http://dx.doi.org/10.1155/2019/5748923
spellingShingle Ling Hou
Dongyan Chen
Chan He
Finite-Time Nonfragile Dissipative Control for Discrete-Time Neural Networks with Markovian Jumps and Mixed Time-Delays
Complexity
title Finite-Time Nonfragile Dissipative Control for Discrete-Time Neural Networks with Markovian Jumps and Mixed Time-Delays
title_full Finite-Time Nonfragile Dissipative Control for Discrete-Time Neural Networks with Markovian Jumps and Mixed Time-Delays
title_fullStr Finite-Time Nonfragile Dissipative Control for Discrete-Time Neural Networks with Markovian Jumps and Mixed Time-Delays
title_full_unstemmed Finite-Time Nonfragile Dissipative Control for Discrete-Time Neural Networks with Markovian Jumps and Mixed Time-Delays
title_short Finite-Time Nonfragile Dissipative Control for Discrete-Time Neural Networks with Markovian Jumps and Mixed Time-Delays
title_sort finite time nonfragile dissipative control for discrete time neural networks with markovian jumps and mixed time delays
url http://dx.doi.org/10.1155/2019/5748923
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AT dongyanchen finitetimenonfragiledissipativecontrolfordiscretetimeneuralnetworkswithmarkovianjumpsandmixedtimedelays
AT chanhe finitetimenonfragiledissipativecontrolfordiscretetimeneuralnetworkswithmarkovianjumpsandmixedtimedelays