Family of iterative LS-based dictionary learning algorithms, ILS-DLA, for sparse signal representation

@article{Engan2007FamilyOI,
  title={Family of iterative LS-based dictionary learning algorithms, ILS-DLA, for sparse signal representation},
  author={Kjersti Engan and Karl Skretting and John H{\aa}kon Hus\oy},
  journal={Digital Signal Processing},
  year={2007},
  volume={17},
  pages={32-49}
}
The use of overcomplete dictionaries, or frames, for sparse signal representation has been given considerable attention in recent years. The major challenges are good algorithms for sparse approximations, i.e., vector selection algorithms, and good methods for choosing or designing dictionaries/frames. This work is concerned with the latter. We present a family of iterative least squares based dictionary learning algorithms (ILS-DLA), including algorithms for design of signal dependent block… CONTINUE READING
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