State estimation for neural networks with leakage delay and time-varying delays
type: Item
instance of: scholarly article
title: State estimation for neural networks with leakage delay and time-varying delays
zbMATH Open document ID: 1288.92005
DOI: 10.1155/2013/289526
author: Jing Liang
author: Zeng-Shun Chen
author: Qiankun Song
published in: Abstract and Applied Analysis
publication date: 2014-06-23T00:00:00Z
review text: Summary: The state estimation problem is investigated for neural networks with leakage and time-varying delays 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.
Mathematics Subject Classification ID: 92B20
Mathematics Subject Classification ID: 62M45
zbMATH DE Number: 6306612
Wikidata QID: Q58915832
MaRDI profile type: Publication
full work available at URL: https://doi.org/10.1155/2013/289526
OpenAlex ID: W1989184079
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description: scientific article; zbMATH DE number 6306612