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A Fast Approach for Overcomplete Sparse Decomposition Based on Smoothed $\ell ^{0}$ Norm
Open accessAbstract
In this paper, a fast algorithm for overcomplete sparse decomposition, called SL0, is proposed. The algorithm is essentially a method for obtaining sparse solutions of underdetermined systems of linear equations, and its applications include underdetermined sparse component analysis (SCA), atomic decomposition on overcomplete dictionaries, compressed sensing, and decoding real field codes. Contrary to previous methods, which usually solve this problem by minimizing thel1norm using linear programming (LP) techniques, our algorithm tries to directly minimize thel1norm. It is experimentally shown that the proposed algorithm is about two to three orders of magnitude faster than the state-of-the-art interior-point LP solvers, while providing the same (or better) accuracy.
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Cited by
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Zhang, Z., Jung, T.-P., Makeig, S., & Rao, B. D. (2013) · IEEE Transactions on Biomedical Engineering · doi:10.1109/tbme.2012.2226175 · Cited by 340
Image Super-Resolution With Sparse Neighbor Embedding
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Metadata
- Authors
- Mohimani, H., Babaie-Zadeh, M., & Jutten, C.
- Venue
- IEEE Transactions on Signal Processing
- Published
- 2009-01
- Volume
- 57
- Issue
- 1
- Pages
- 289-301
- ISSN
- 1053-587X (ISSN-L)
- 1941-0476
- OpenAlex
- W2100068253
- Cited by
- 1,091
- References
- 0
- FWCI
- 38.16
- Type
- journal article
- Language
- en
- Open access
- green
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- Mohimani, H., Babaie-Zadeh, M., & Jutten, C. (2009). A Fast Approach for Overcomplete Sparse Decomposition Based on Smoothed $\ell ^{0}$ Norm. IEEE Transactions on Signal Processing. https://doi.org/10.1109/tsp.2008.2007606
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