Sparse Spectral Estimation
Sparse Spectral Estimation is a spectral analysis method that exploits sparsity in the frequency domain by modeling the power spectrum as a sparse combination of basis elements, enabling high-resolution frequency recovery from limited or undersampled data.
169
Publications
6.4K
Citations
490
Authors
238
Institutions
Publications per year
2017–2026
46
Parents
169
Spectral Unmixing via Data-Guided Sparsity
Feiyun Zhu, Ying Wang, Bin Fan et al. · IEEE Transactions on Image Processing · 2014 · 274 citations · Full text
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238

Lund University
Lund, Sweden
8 h-index
18 publications
358 citations

Centre National de la Recherche Scientifique
Paris, France
8 h-index
11 publications
309 citations
Statistics Sweden
Örebro, Sweden
7 h-index
13 publications
283 citations

University of Electronic Science and Technology of China
Chengdu, China
5 h-index
13 publications
264 citations

Chinese Academy of Sciences
Beijing, China
5 h-index
18 publications
2K citations

University of Minnesota
Minneapolis, United States
5 h-index
12 publications
468 citations
Princeton University
Princeton, United States
4 h-index
4 publications
132 citations
University of Florida
Gainesville, United States
4 h-index
11 publications
349 citations
1–8 of 238
15 publications · 1.3K citations
14
h-index
14 publications · 441 citations
11
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JMR · 5 publications · 177 citations
5
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Repository · 5 publications · 95 citations
5
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MSSP · 5 publications · 144 citations
5
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1–5