File Download

There are no files associated with this item.

  Links for fulltext
     (May Require Subscription)
Supplementary

Conference Paper: High-resolution time-frequency analysis of somatosensory evoked potential components by means of matching pursuit

TitleHigh-resolution time-frequency analysis of somatosensory evoked potential components by means of matching pursuit
Authors
KeywordsTime Domain Analysis
Issue Date2008
Citation
International Conference On Signal Processing Proceedings, Icsp, 2008, p. 153-156 How to Cite?
AbstractThis paper proposes to apply a high-resolution time-frequency analysis (TFA) algorithm, the matching pursuit (MP), to extract and identify detail components of somatosensory evoked potential (SEP) signals. Conventional TFA methods showed limited timefrequency resolution in short-period nonstationary SEP signals so that they cannot reveal detail components in time-frequency domain. The MP algorithm can decompose a SEP signal into a number of elementary components and provide a time-frequency parameter description of decomposed components. The stable components can be revealed by statistical analysis and classification of the extracted parameters. Experimental results on cortical SEP signals of rats show that a series of stable SEP components can be identified using the MP decomposition algorithm. © 2008 IEEE.
Persistent Identifierhttp://hdl.handle.net/10722/143329
References

 

DC FieldValueLanguage
dc.contributor.authorHu, Yen_HK
dc.contributor.authorZhang, ZGen_HK
dc.contributor.authorChan, SCen_HK
dc.contributor.authorLuk, KDKen_HK
dc.date.accessioned2011-11-22T08:30:34Z-
dc.date.available2011-11-22T08:30:34Z-
dc.date.issued2008en_HK
dc.identifier.citationInternational Conference On Signal Processing Proceedings, Icsp, 2008, p. 153-156en_HK
dc.identifier.urihttp://hdl.handle.net/10722/143329-
dc.description.abstractThis paper proposes to apply a high-resolution time-frequency analysis (TFA) algorithm, the matching pursuit (MP), to extract and identify detail components of somatosensory evoked potential (SEP) signals. Conventional TFA methods showed limited timefrequency resolution in short-period nonstationary SEP signals so that they cannot reveal detail components in time-frequency domain. The MP algorithm can decompose a SEP signal into a number of elementary components and provide a time-frequency parameter description of decomposed components. The stable components can be revealed by statistical analysis and classification of the extracted parameters. Experimental results on cortical SEP signals of rats show that a series of stable SEP components can be identified using the MP decomposition algorithm. © 2008 IEEE.en_HK
dc.languageengen_US
dc.relation.ispartofInternational Conference on Signal Processing Proceedings, ICSPen_HK
dc.subjectTime Domain Analysisen_US
dc.titleHigh-resolution time-frequency analysis of somatosensory evoked potential components by means of matching pursuiten_HK
dc.typeConference_Paperen_HK
dc.identifier.emailHu, Y:yhud@hku.hken_HK
dc.identifier.emailZhang, ZG:zgzhang@eee.hku.hken_HK
dc.identifier.emailChan, SC:scchan@eee.hku.hken_HK
dc.identifier.emailLuk, KDK:hcm21000@hku.hken_HK
dc.identifier.authorityHu, Y=rp00432en_HK
dc.identifier.authorityZhang, ZG=rp01565en_HK
dc.identifier.authorityChan, SC=rp00094en_HK
dc.identifier.authorityLuk, KDK=rp00333en_HK
dc.description.naturelink_to_subscribed_fulltexten_US
dc.identifier.doi10.1109/ICOSP.2008.4697092en_HK
dc.identifier.scopuseid_2-s2.0-67249148188en_HK
dc.relation.referenceshttp://www.scopus.com/mlt/select.url?eid=2-s2.0-67249148188&selection=ref&src=s&origin=recordpageen_HK
dc.identifier.spage153en_HK
dc.identifier.epage156en_HK
dc.identifier.scopusauthoridHu, Y=7407116091en_HK
dc.identifier.scopusauthoridZhang, ZG=8597618700en_HK
dc.identifier.scopusauthoridChan, SC=13310287100en_HK
dc.identifier.scopusauthoridLuk, KDK=7201921573en_HK
dc.identifier.citeulike8152757-

Export via OAI-PMH Interface in XML Formats


OR


Export to Other Non-XML Formats