Cooperative greedy pursuit strategies for sparse signal representation by partitioning

Laura Rebollo-Neira*

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review


Cooperative Greedy Pursuit Strategies are considered for approximating a signal partition subjected to a global constraint on sparsity. The approach aims at producing a high quality sparse approximation of the whole signal, using highly coherent redundant dictionaries. The cooperation takes place by ranking the partition units for their sequential stepwise approximation, and is realized by means of i)forward steps for the upgrading of an approximation and/or ii) backward steps for the corresponding downgrading. The advantage of the strategy is illustrated by approximation of music signals using redundant trigonometric dictionaries. In addition to rendering stunning improvements in sparsity with respect to the concomitant trigonometric basis, these dictionaries enable a fast implementation of the approach via the Fast Fourier Transform
Original languageEnglish
Pages (from-to)365-375
Number of pages11
JournalSignal processing
Early online date16 Feb 2016
Publication statusPublished - Aug 2016

Bibliographical note

© 2016, Elsevier. Licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International


  • cooperation greedy pursuit strategies
  • sparse representation of music signals by partitioning
  • trigonometric dictionaries


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