The DOI matches its Crossref record; 4 of the 4 references it cites were found in a registry or an index.
Matching pursuits with time-frequency dictionaries
Abstract
The authors introduce an algorithm, called matching pursuit, that decomposes any signal into a linear expansion of waveforms that are selected from a redundant dictionary of functions. These waveforms are chosen in order to best match the signal structures. Matching pursuits are general procedures to compute adaptive signal representations. With a dictionary of Gabor functions a matching pursuit defines an adaptive time-frequency transform. They derive a signal energy distribution in the time-frequency plane, which does not include interference terms, unlike Wigner and Cohen class distributions. A matching pursuit isolates the signal structures that are coherent with respect to a given dictionary. An application to pattern extraction from noisy signals is described. They compare a matching pursuit decomposition with a signal expansion over an optimized wavepacket orthonormal basis, selected with the algorithm of Coifman and Wickerhauser see (IEEE Trans. Informat. Theory, vol. 38, Mar. 1992).>
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Cites
Golub, G. (2012) · doi:10.56021/9781421407944 · Cited by 34,505
Daubechies, I. (1992) · doi:10.1137/1.9781611970104 · Cited by 15,979
The wavelet transform, time-frequency localization and signal analysis
Daubechies, I. (1990) · IEEE Transactions on Information Theory · doi:10.1109/18.57199 · Cited by 6,483
Huber, P. J. (1985) · The Annals of Statistics · doi:10.1214/aos/1176349519 · Cited by 1,277
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Image Denoising Via Sparse and Redundant Representations Over Learned Dictionaries
Elad, M., & Aharon, M. (2006) · IEEE Transactions on Image Processing · doi:10.1109/tip.2006.881969 · Cited by 5,321
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Metadata
- Authors
- Mallat, S. G., & Zhang, Z.
- Venue
- IEEE Transactions on Signal Processing
- Published
- 1993
- Volume
- 41
- Issue
- 12
- Pages
- 3397-3415
- ISSN
- 1053-587X (ISSN-L)
- OpenAlex
- W2151693816
- Cited by
- 9,112
- References
- 4
- FWCI
- 45.99
- Type
- journal article
- Language
- en
- Open access
- closed
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