An iterative subspace-based multi-pitch estimation algorithm
In this paper, we present an iterative method for estimation of pitches from signals containing multiple sources using subspace techniques. The resulting estimator is termed Iterative Harmonic MUltiple SIgnal Classification (I-HMUSIC). Different modifications of I-HMUSIC are proposed that improve up...
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| Veröffentlicht in: | Signal processing 2011, Vol.91 (1), p.150-154 |
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| container_title | Signal processing |
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| creator | Zhang, Johan Xi Christensen, Mads Græsbøll Jensen, Søren Holdt Moonen, Marc |
| description | In this paper, we present an iterative method for estimation of pitches from signals containing multiple sources using subspace techniques. The resulting estimator is termed Iterative Harmonic MUltiple SIgnal Classification (I-HMUSIC). Different modifications of I-HMUSIC are proposed that improve upon the classical MUSIC algorithm, including a computationally efficient method for noise subspace updating I-HMUSIC and its modifications are evaluated and compared with both the Cramér–Rao lower bound (CRLB) and non-iterative HMUSIC; good statistical performances have been obtained. |
| doi_str_mv | 10.1016/j.sigpro.2010.06.010 |
| format | Article |
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The resulting estimator is termed Iterative Harmonic MUltiple SIgnal Classification (I-HMUSIC). Different modifications of I-HMUSIC are proposed that improve upon the classical MUSIC algorithm, including a computationally efficient method for noise subspace updating I-HMUSIC and its modifications are evaluated and compared with both the Cramér–Rao lower bound (CRLB) and non-iterative HMUSIC; good statistical performances have been obtained.</description><identifier>ISSN: 0165-1684</identifier><identifier>EISSN: 1872-7557</identifier><identifier>DOI: 10.1016/j.sigpro.2010.06.010</identifier><identifier>CODEN: SPRODR</identifier><language>eng</language><publisher>Amsterdam: Elsevier B.V</publisher><subject>Algorithms ; Applied sciences ; Computational efficiency ; Cyclic minimizer ; Detection, estimation, filtering, equalization, prediction ; Estimators ; Exact sciences and technology ; Information, signal and communications theory ; Iterative methods ; Lower bounds ; Multi-pitch estimation ; Noise ; Noise subspace ; Orthogonality ; Signal and communications theory ; Signal classification ; Signal processing ; Signal representation. 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The resulting estimator is termed Iterative Harmonic MUltiple SIgnal Classification (I-HMUSIC). 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Spectral analysis</topic><topic>Signal, noise</topic><topic>Subspaces</topic><topic>Telecommunications and information theory</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Zhang, Johan Xi</creatorcontrib><creatorcontrib>Christensen, Mads Græsbøll</creatorcontrib><creatorcontrib>Jensen, Søren Holdt</creatorcontrib><creatorcontrib>Moonen, Marc</creatorcontrib><collection>Pascal-Francis</collection><collection>CrossRef</collection><collection>Computer and Information Systems Abstracts</collection><collection>Electronics & Communications Abstracts</collection><collection>Technology Research Database</collection><collection>ProQuest Computer Science Collection</collection><collection>Advanced Technologies Database with Aerospace</collection><collection>Computer and Information Systems Abstracts Academic</collection><collection>Computer and Information Systems Abstracts Professional</collection><jtitle>Signal processing</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Zhang, Johan Xi</au><au>Christensen, Mads Græsbøll</au><au>Jensen, Søren Holdt</au><au>Moonen, Marc</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>An iterative subspace-based multi-pitch estimation algorithm</atitle><jtitle>Signal processing</jtitle><date>2011</date><risdate>2011</risdate><volume>91</volume><issue>1</issue><spage>150</spage><epage>154</epage><pages>150-154</pages><issn>0165-1684</issn><eissn>1872-7557</eissn><coden>SPRODR</coden><abstract>In this paper, we present an iterative method for estimation of pitches from signals containing multiple sources using subspace techniques. 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| fulltext | fulltext |
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| ispartof | Signal processing, 2011, Vol.91 (1), p.150-154 |
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| source | Elsevier ScienceDirect Journals |
| subjects | Algorithms Applied sciences Computational efficiency Cyclic minimizer Detection, estimation, filtering, equalization, prediction Estimators Exact sciences and technology Information, signal and communications theory Iterative methods Lower bounds Multi-pitch estimation Noise Noise subspace Orthogonality Signal and communications theory Signal classification Signal processing Signal representation. Spectral analysis Signal, noise Subspaces Telecommunications and information theory |
| title | An iterative subspace-based multi-pitch estimation algorithm |
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