State Estimation for Neural Networks with Leakage Delay and Time-Varying Delays

The state estimation problem is investigated for neural networks with leakage delay and time-varying delay as well as for general activation functions. By constructing appropriate Lyapunov-Krasovskii functionals and employing matrix inequality techniques, a delay-dependent linear matrix inequalities...

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Main Authors: Jing Liang, Zengshun Chen, Qiankun Song
Format: Article
Language:English
Published: Wiley 2013-01-01
Series:Abstract and Applied Analysis
Online Access:http://dx.doi.org/10.1155/2013/289526
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author Jing Liang
Zengshun Chen
Qiankun Song
author_facet Jing Liang
Zengshun Chen
Qiankun Song
author_sort Jing Liang
collection DOAJ
description The state estimation problem is investigated for neural networks with leakage delay and time-varying delay as well as for general activation functions. By constructing appropriate Lyapunov-Krasovskii functionals and employing matrix inequality techniques, a delay-dependent linear matrix inequalities (LMIs) condition is developed to estimate the neuron state with some observed output measurements such that the error-state system is globally asymptotically stable. An example is given to show the effectiveness of the proposed criterion.
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institution Kabale University
issn 1085-3375
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language English
publishDate 2013-01-01
publisher Wiley
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series Abstract and Applied Analysis
spelling doaj-art-5ae856533c2a44d1a7c11d02766489a82025-02-03T00:59:21ZengWileyAbstract and Applied Analysis1085-33751687-04092013-01-01201310.1155/2013/289526289526State Estimation for Neural Networks with Leakage Delay and Time-Varying DelaysJing Liang0Zengshun Chen1Qiankun Song2Department of Mathematics, Chongqing Jiaotong University, Chongqing 400074, ChinaSchool of Civil Engineering & Architecture, Chongqing Jiaotong University, Chongqing 400074, ChinaDepartment of Mathematics, Chongqing Jiaotong University, Chongqing 400074, ChinaThe state estimation problem is investigated for neural networks with leakage delay and time-varying delay as well as for general activation functions. By constructing appropriate Lyapunov-Krasovskii functionals and employing matrix inequality techniques, a delay-dependent linear matrix inequalities (LMIs) condition is developed to estimate the neuron state with some observed output measurements such that the error-state system is globally asymptotically stable. An example is given to show the effectiveness of the proposed criterion.http://dx.doi.org/10.1155/2013/289526
spellingShingle Jing Liang
Zengshun Chen
Qiankun Song
State Estimation for Neural Networks with Leakage Delay and Time-Varying Delays
Abstract and Applied Analysis
title State Estimation for Neural Networks with Leakage Delay and Time-Varying Delays
title_full State Estimation for Neural Networks with Leakage Delay and Time-Varying Delays
title_fullStr State Estimation for Neural Networks with Leakage Delay and Time-Varying Delays
title_full_unstemmed State Estimation for Neural Networks with Leakage Delay and Time-Varying Delays
title_short State Estimation for Neural Networks with Leakage Delay and Time-Varying Delays
title_sort state estimation for neural networks with leakage delay and time varying delays
url http://dx.doi.org/10.1155/2013/289526
work_keys_str_mv AT jingliang stateestimationforneuralnetworkswithleakagedelayandtimevaryingdelays
AT zengshunchen stateestimationforneuralnetworkswithleakagedelayandtimevaryingdelays
AT qiankunsong stateestimationforneuralnetworkswithleakagedelayandtimevaryingdelays