Robust adaptive techniques for minimization of EOG artefacts from EEG signals

In this paper, we propose the application of H ∞ techniques for minimization of electrooculogram (EOG) artefacts from corrupted electroencephalographic (EEG) signals. Two adaptive algorithms ( time-varying and exponentially-weighted) based on the H ∞ principles are proposed. The idea of applying H ∞...

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Veröffentlicht in:	Signal processing Jg. 86; H. 9; S. 2351 - 2363
Hauptverfasser:	Puthusserypady, S., Ratnarajah, T.
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	Amsterdam Elsevier B.V 01.09.2006 Elsevier Science
Schlagworte:	Applied sciences Biological and medical sciences Computerized, statistical medical data processing and models in biomedicine Detection, estimation, filtering, equalization, prediction Electroencephalogram (EEG) Electrooculogram (EOG) artefacts Exact sciences and technology Information, signal and communications theory Medical management aid. Diagnosis aid Medical sciences Robust adaptive filtering Signal and communications theory Signal, noise Telecommunications and information theory Electrooculogram (EOG) artefacts Robust adaptive filtering Electroencephalogram (EEG) Performance evaluation H infinite optimization Adaptive algorithm Adaptive filtering Artefact Electroencephalography Output signal Recursive algorithm Adaptive method Time variation Robust control Algorithm performance Least squares method Recursive method Linear estimation Least mean squares methods Signal to noise ratio
ISSN:	0165-1684, 1872-7557
Online-Zugang:	Volltext
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