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dc.contributor.authorReig Bolano, Ramon
dc.contributor.authorMarti Puig, Pere
dc.contributor.authorSolé-Casals, Jordi
dc.contributor.authorZaiats, Vladimir
dc.contributor.authorParisi Baradad, Vicenç
dc.contributor.otherUniversitat Politècnica de Catalunya. Departament d'Enginyeria Electrònica
dc.date.accessioned2011-12-19T13:00:04Z
dc.date.available2011-12-19T13:00:04Z
dc.date.created2009
dc.date.issued2009
dc.identifier.citationReig, R. [et al.]. Coding of biosignals using the discrete wavelet decomposition. A: International conference on non-linear speech processing. "Advances in nonlinear speech processing : international conference on nonlinear speech processing, NOLISP 2009 : Vic, Spain, June 25-27, 2009 : revised selected papers". Vic: Springer, 2009, p. 144-151.
dc.identifier.isbn978-3-642-11508-0
dc.identifier.urihttp://hdl.handle.net/2117/14273
dc.description.abstractWavelet derived codification techniques are widespread used in image codifiers. The wavelet based compression methods are adequate for representing transients. In this paper we explore the use of the discrete wavelet transform analysis of biological signals in order to improve the data compression capability of data coders. The wavelet analysis provides a subband decomposition of any signal, and this enables a lossless or a lossy implementation with the same architecture. The signals could range from speech to sounds or music, but the approach is more orientated to other biosignals like medical signals EEG, ECG or discrete series. Experimental results based on wavelet coefficients quantification, show a lossless compression of 2:1 in all kind of signals, with a fidelity, measured using PSNR, from 79dB to 100dB, and lossy results preserving most of the signal waveform, with a compression ratio from 3:1 to 5:1, with a fidelity from 25dB to 35 dB.
dc.format.extent8 p.
dc.language.isoeng
dc.publisherSpringer
dc.subjectÀrees temàtiques de la UPC::Enginyeria de la telecomunicació::Telemàtica i xarxes d'ordinadors::Trànsit de dades
dc.subject.lcshData compression (Computer science)
dc.subject.lcshWavelets (Mathematics)--Data processing
dc.titleCoding of biosignals using the discrete wavelet decomposition
dc.typeConference report
dc.subject.lemacTren d'ones (Matemàtica)
dc.subject.lemacDades -- Compressió (Informàtica)
dc.subject.lemacWavelets (Matemàtica)
dc.subject.lemacOnes (Matemàtica)
dc.identifier.doi10.1007/978-3-642-11509-7_19
dc.description.peerreviewedPeer Reviewed
dc.rights.accessRestricted access - publisher's policy
local.identifier.drac8817171
dc.description.versionPostprint (published version)
local.citation.authorReig, R.; Marti, P.; Solé-Casals, J.; Zaiats, V.; Parisi, V.
local.citation.contributorInternational conference on non-linear speech processing
local.citation.pubplaceVic
local.citation.publicationNameAdvances in nonlinear speech processing : international conference on nonlinear speech processing, NOLISP 2009 : Vic, Spain, June 25-27, 2009 : revised selected papers
local.citation.startingPage144
local.citation.endingPage151


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