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https://hdl.handle.net/2440/77904
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DC Field | Value | Language |
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dc.contributor.author | Wu, Z. | - |
dc.contributor.author | Shi, P. | - |
dc.contributor.author | Su, H. | - |
dc.contributor.author | Chu, J. | - |
dc.date.issued | 2012 | - |
dc.identifier.citation | International Journal of Systems Science, 2012; 43(4):647-655 | - |
dc.identifier.issn | 0020-7721 | - |
dc.identifier.issn | 1464-5319 | - |
dc.identifier.uri | http://hdl.handle.net/2440/77904 | - |
dc.description.abstract | This article deals with the problem of delay-dependent state estimation for discrete-time neural networks with time-varying delay. Our objective is to design a state estimator for the neuron states through available output measurements such that the error state system is guaranteed to be globally exponentially stable. Based on the linear matrix inequality approach, a delay-dependent condition is developed for the existence of the desired state estimator via a novel Lyapunov functional. The obtained condition has less conservativeness than the existing ones, which is demonstrated by a numerical example. | - |
dc.description.statementofresponsibility | Zhengguang Wu, Peng Shi, Hongye Su and Jian Chu | - |
dc.language.iso | en | - |
dc.publisher | Taylor & Francis Ltd | - |
dc.rights | © 2012 Taylor & Francis | - |
dc.source.uri | http://dx.doi.org/10.1080/00207721.2010.517870 | - |
dc.subject | neural networks | - |
dc.subject | time-varying delay | - |
dc.subject | state estimation | - |
dc.subject | exponential stability | - |
dc.subject | linear matrix inequality (LMI) | - |
dc.title | State estimation for discrete-time neural networks with time-varying delay | - |
dc.type | Journal article | - |
dc.identifier.doi | 10.1080/00207721.2010.517870 | - |
pubs.publication-status | Published | - |
dc.identifier.orcid | Shi, P. [0000-0001-8218-586X] | - |
Appears in Collections: | Aurora harvest 4 Electrical and Electronic Engineering publications |
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