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A SVD-based classif...
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Sandsten, MariaLund University,Lunds universitet,Statistical Signal Processing Group,Forskargrupper vid Lunds universitet,Matematisk statistik,Matematikcentrum,Institutioner vid LTH,Lunds Tekniska Högskola,Lund University Research Groups,Mathematical Statistics,Centre for Mathematical Sciences,Departments at LTH,Faculty of Engineering, LTH
(författare)
A SVD-based classification of bird singing in different time-frequency domains using multitapers
- Artikel/kapitelEngelska2011
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LIBRIS-ID:oai:lup.lub.lu.se:d9e2f018-bd60-4a65-b4af-ec66c7fc1b54
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https://lup.lub.lu.se/record/2225102URI
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Språk:engelska
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Sammanfattning på:engelska
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In this paper, a novel method for analysing a bird’s song is presented. The song of male great reed warblers is used for developing and testing the methods. A robust method for detecting syllables is proposed and a classification of those syllables as compared to reference syllables is done. The extraction of classification features are based on the use of singular vectors in different time-frequency domains, such as the ambiguity and the doppler domains, in addition to the usual sonogram. The analysis is also made using multitaper analysis where the Welch method and the Thomson multi- tapers are compared to the more recently proposed locally stationary process multitapers.
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Tarka, MajaLund University,Lunds universitet,MEMEG,Biologiska institutionen,Naturvetenskapliga fakulteten,Department of Biology,Faculty of Science(Swepub:lu)zooe-mat
(författare)
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Caissy-Martineau, Jessica
(författare)
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Hansson, BengtLund University,Lunds universitet,MEMEG,Biologiska institutionen,Naturvetenskapliga fakulteten,Department of Biology,Faculty of Science(Swepub:lu)ekol-bhn
(författare)
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Hasselquist, DennisLund University,Lunds universitet,MEMEG,Biologiska institutionen,Naturvetenskapliga fakulteten,Department of Biology,Faculty of Science(Swepub:lu)ekol-dha
(författare)
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Statistical Signal Processing GroupForskargrupper vid Lunds universitet
(creator_code:org_t)
Sammanhörande titlar
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Ingår i:European Signal Processing Conference2011, s. 966-9702219-5491
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