Time Recursive Multi-Pitch Estimation Using Group Sparse Recursive Least Squares

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In this work, we propose a time-recursive multi-pitch estimation algorithm, using a sparse reconstruction framework, assuming
only a few pitches from a large set of candidates to be active at each time instant. The proposed algorithm utilizes a sparse
recursive least squares formulation augmented by an adaptive penalty term specifically designed to enforce a pitch structure on
the solution. When evaluated on a set of ten music pieces, the proposed method is shown to outperform state-of-the-art multi-
pitch estimators in either accuracy or computational spe
Titel på värdpublikation50th Asilomar Conference on Signals, Systems, and Computers, 2016
FörlagIEEE - Institute of Electrical and Electronics Engineers Inc.
Antal sidor5
ISBN (elektroniskt)978-1-5386-3954-2
StatusPublished - 2017
Evenemang50th Annual Asilomar Conference on Signals, Systems, and Computers (ASILOMAR 2016) - Asilomar Hotel & Conference Grounds, Pacific Grove, USA
Varaktighet: 2016 nov. 62016 nov. 9


Konferens50th Annual Asilomar Conference on Signals, Systems, and Computers (ASILOMAR 2016)
OrtPacific Grove

Ämnesklassifikation (UKÄ)

  • Sannolikhetsteori och statistik
  • Signalbehandling

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