Abstract
The uncertainty principle can easily be generalized to cases where the “sets of concentration” are not intervals. Such generalizations are presented for continuous and discrete-time functions, and for several measures of “concentration” (e.g., $L_2 $ and $L_1 $ measures). The generalizations explain interesting phenomena in signal recovery problems where there is an interplay of missing data, sparsity, and bandlimiting.
Keywords
Signal recoverySIGNAL (programming language)MathematicsApplied mathematicsCalculus (dental)Computer scienceAlgorithmCompressed sensing
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Publication Info
- Year
- 1989
- Type
- article
- Volume
- 49
- Issue
- 3
- Pages
- 906-931
- Citations
- 1041
- Access
- Closed
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Cite This
David L. Donoho,
Philip B. Stark
(1989).
Uncertainty Principles and Signal Recovery.
SIAM Journal on Applied Mathematics
, 49
(3)
, 906-931.
https://doi.org/10.1137/0149053
Identifiers
- DOI
- 10.1137/0149053