Iterative Hard Thresholding and L0 Regularisation
Sparse signal approximations are approximations that use only a small number of elementary waveforms to describe a signal. In this paper we proof the convergence of an iterative hard thresholding algorithm and show, that the fixed points of that algorithm are local minima of the sparse approximation...
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| Veröffentlicht in: | 2007 IEEE International Conference on Acoustics, Speech and Signal Processing - ICASSP '07 Jg. 3; S. III-877 - III-880 |
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| Format: | Tagungsbericht |
| Sprache: | Englisch |
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IEEE
01.04.2007
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| ISBN: | 9781424407279, 1424407273 |
| ISSN: | 1520-6149 |
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| Abstract | Sparse signal approximations are approximations that use only a small number of elementary waveforms to describe a signal. In this paper we proof the convergence of an iterative hard thresholding algorithm and show, that the fixed points of that algorithm are local minima of the sparse approximation cost function, which measures both, the reconstruction error and the number of elements in the representation. Simulation results suggest that the algorithm is comparable in performance to a commonly used alternative method. |
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| AbstractList | Sparse signal approximations are approximations that use only a small number of elementary waveforms to describe a signal. In this paper we proof the convergence of an iterative hard thresholding algorithm and show, that the fixed points of that algorithm are local minima of the sparse approximation cost function, which measures both, the reconstruction error and the number of elements in the representation. Simulation results suggest that the algorithm is comparable in performance to a commonly used alternative method. |
| Author | Yaghoobi, M. Blumensath, T. Davies, M.E. |
| Author_xml | – sequence: 1 givenname: T. surname: Blumensath fullname: Blumensath, T. organization: IDCOM & Joint Res. Inst. for Signal & Image Process., Edinburgh Univ – sequence: 2 givenname: M. surname: Yaghoobi fullname: Yaghoobi, M. organization: IDCOM & Joint Res. Inst. for Signal & Image Process., Edinburgh Univ – sequence: 3 givenname: M.E. surname: Davies fullname: Davies, M.E. organization: IDCOM & Joint Res. Inst. for Signal & Image Process., Edinburgh Univ |
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| Snippet | Sparse signal approximations are approximations that use only a small number of elementary waveforms to describe a signal. In this paper we proof the... |
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| StartPage | III-877 |
| SubjectTerms | Approximation algorithms Convergence Cost function Equations Iterative algorithms Iterative Thresholding L0 Regularisation Matching pursuit algorithms Noise reduction Pursuit algorithms Signal processing Signal processing algorithms Sparse Approximations |
| Title | Iterative Hard Thresholding and L0 Regularisation |
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