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Conference Paper: Adaptive window selection and smoothing of Lomb periodogram for time-frequency analysis of time series

TitleAdaptive window selection and smoothing of Lomb periodogram for time-frequency analysis of time series
Authors
KeywordsComputers
Circuits
Issue Date2004
PublisherIEEE.
Citation
Midwest Symposium On Circuits And Systems, 2004, v. 2, p. II137-II140 How to Cite?
AbstractThis article introduces a new adaptive Lomb periodogram for time-frequency analysis of time series, which are possibly non-uniformly sampled. It extends the conventional Lomb spectrum by windowing the observations and adaptively selects the window length by the intersection of confidence intervals (ICI) rule. To further reduce the variance of the Lomb periodogram due to time smoothing alone, time-frequency smoothing using local polynomial regression (LPR) is proposed. An orientation analysis is performed in order to derive a directional kernel in the time-frequency plane for adaptive smoothing of the periodogram. The support of this directional kernel is also adaptively selected using the ICI rule. Simulation results show that the proposed adaptive Lomb periodogram with time-frequency smoothing offers better time and frequency resolutions as well as lower variance than the conventional Lomb periodogram.
DescriptionThe 47th Midwest Symposium on Circuits and Systems Conference, Salt Lake City, Utah, USA, 25-28 July 2004
Persistent Identifierhttp://hdl.handle.net/10722/46438
ISSN
References

 

DC FieldValueLanguage
dc.contributor.authorChan, SCen_HK
dc.contributor.authorZhang, Zen_HK
dc.date.accessioned2007-10-30T06:49:51Z-
dc.date.available2007-10-30T06:49:51Z-
dc.date.issued2004en_HK
dc.identifier.citationMidwest Symposium On Circuits And Systems, 2004, v. 2, p. II137-II140en_HK
dc.identifier.issn1548-3746en_HK
dc.identifier.urihttp://hdl.handle.net/10722/46438-
dc.descriptionThe 47th Midwest Symposium on Circuits and Systems Conference, Salt Lake City, Utah, USA, 25-28 July 2004-
dc.description.abstractThis article introduces a new adaptive Lomb periodogram for time-frequency analysis of time series, which are possibly non-uniformly sampled. It extends the conventional Lomb spectrum by windowing the observations and adaptively selects the window length by the intersection of confidence intervals (ICI) rule. To further reduce the variance of the Lomb periodogram due to time smoothing alone, time-frequency smoothing using local polynomial regression (LPR) is proposed. An orientation analysis is performed in order to derive a directional kernel in the time-frequency plane for adaptive smoothing of the periodogram. The support of this directional kernel is also adaptively selected using the ICI rule. Simulation results show that the proposed adaptive Lomb periodogram with time-frequency smoothing offers better time and frequency resolutions as well as lower variance than the conventional Lomb periodogram.en_HK
dc.format.extent460880 bytes-
dc.format.extent27162 bytes-
dc.format.mimetypeapplication/pdf-
dc.format.mimetypetext/plain-
dc.languageengen_HK
dc.publisherIEEE.en_HK
dc.relation.ispartofMidwest Symposium on Circuits and Systemsen_HK
dc.rightsCreative Commons: Attribution 3.0 Hong Kong License-
dc.rights©2004 IEEE. Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE.en_HK
dc.subjectComputersen_HK
dc.subjectCircuitsen_HK
dc.titleAdaptive window selection and smoothing of Lomb periodogram for time-frequency analysis of time seriesen_HK
dc.typeConference_Paperen_HK
dc.identifier.openurlhttp://library.hku.hk:4550/resserv?sid=HKU:IR&issn=1548-3746&volume=2&spage=137&epage=140&date=2004&atitle=Adaptive+window+selection+and+smoothing+of+Lomb+periodogram+for+time-frequency+analysis+of+time+seriesen_HK
dc.identifier.emailChan, SC:scchan@eee.hku.hken_HK
dc.identifier.emailZhang, Z:zgzhang@eee.hku.hken_HK
dc.identifier.authorityChan, SC=rp00094en_HK
dc.identifier.authorityZhang, Z=rp01565en_HK
dc.description.naturepublished_or_final_versionen_HK
dc.identifier.doi10.1109/MWSCAS.2004.1354110en_HK
dc.identifier.scopuseid_2-s2.0-11144299055en_HK
dc.identifier.hkuros90101-
dc.relation.referenceshttp://www.scopus.com/mlt/select.url?eid=2-s2.0-11144299055&selection=ref&src=s&origin=recordpageen_HK
dc.identifier.volume2en_HK
dc.identifier.spageII137en_HK
dc.identifier.epageII140en_HK
dc.publisher.placeUnited Statesen_HK
dc.identifier.scopusauthoridChan, SC=13310287100en_HK
dc.identifier.scopusauthoridZhang, Z=8597618700en_HK

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