HEAL DSpace

ASYMPTOTIC PROPERTIES OF A NEW RECURSIVE IDENTIFICATION METHOD USING DECONVOLUTION.

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dc.contributor.author Kollias, Stefanos en
dc.contributor.author Halkias, Christos en
dc.date.accessioned 2014-03-01T02:47:36Z
dc.date.available 2014-03-01T02:47:36Z
dc.date.issued 1985 en
dc.identifier.issn 02714310 en
dc.identifier.uri https://dspace.lib.ntua.gr/xmlui/handle/123456789/33277
dc.relation.uri http://www.scopus.com/inward/record.url?eid=2-s2.0-0022307081&partnerID=40&md5=99c9fe32be3cb5bf1c2caea36735d693 en
dc.subject.other COMPUTER PROGRAMMING - Algorithms en
dc.subject.other SEISMOLOGY en
dc.subject.other SIGNAL PROCESSING - Digital Techniques en
dc.subject.other AUTOREGRESSIVE MOVING-AVERAGE PROCESSES en
dc.subject.other DECONVOLUTION en
dc.subject.other INSTRUMENTAL VARIABLES METHOD en
dc.subject.other RECURSIVE IDENTIFICATION en
dc.subject.other SEISMIC SIGNALS en
dc.subject.other SYSTEMS SCIENCE AND CYBERNETICS en
dc.title ASYMPTOTIC PROPERTIES OF A NEW RECURSIVE IDENTIFICATION METHOD USING DECONVOLUTION. en
heal.type conferenceItem en
heal.publicationDate 1985 en
heal.abstract The authors examine the performance of a new recursive identification and deconvolution approach in the case of an ARMA model of a system, whose input is white unmeasurable stationary noise. This approach, which is especially useful in seismic signal deconvolution, is based on an algorithm using the instrumental variables method, combined with an online version of minimum variance deconvolution. The asymptotic properties of each of these two methods are examined in detail and various conclusions are derived. The performance of the method is evaluated in terms of the signal-to-noise ratio and the pole-zero locations or the frequency bandwidth of the impulse response of the system. Examples illustrate the theoretical results. en
heal.publisher IEEE, New York, NY, USA en
heal.journalName Proceedings - IEEE International Symposium on Circuits and Systems en
dc.identifier.spage 419 en
dc.identifier.epage 422 en


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