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Error correction via linear programming
Abstract
Suppose we wish to transmit a vector f ϵ Rnreliably. A frequently discussed approach consists in encoding f with an m by n coding matrix A. Assume now that a fraction of the entries of Af are corrupted in a completely arbitrary fashion by an error e. We do not know which entries are affected nor do we know how they are affected. Is it possible to recover f exactly from the corrupted m-dimensional vector y = Af + e?
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Daubechies, I. (1992) · doi:10.1137/1.9781611970104 · Cited by 15,979
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Analog-to-Information Conversion via Random Demodulation
Kirolos, S., Laska, J., Wakin, M., Duarte, M., Baron, D., Ragheb, T., Massoud, Y., & Baraniuk, R. (2006) · 2006 IEEE Dallas/CAS Workshop on Design, Applications, Integration and Software · doi:10.1109/dcas.2006.321036 · Cited by 393
An Architecture for Compressive Imaging
Wakin, M. B., Laska, J. N., Duarte, M. F., Baron, D., Sarvotham, S., Takhar, D., Kelly, K. F., & Baraniuk, R. G. (2006) · 2006 International Conference on Image Processing · doi:10.1109/icip.2006.312577 · Cited by 323
Metadata
- Authors
- Candes, E., Rudelson, M., Tao, T., & Vershynin, R.
- Venue
- 46th Annual IEEE Symposium on Foundations of Computer Science (FOCS'05)
- Publisher
- IEEE
- Published
- 2005
- Pages
- 668-681
- ISSN
- 0272-5428 (ISSN-L)
- OpenAlex
- W2096185893
- Cited by
- 251
- References
- 1
- FWCI
- 45.73
- Type
- conference paper
- Language
- en
- Open access
- closed
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- Candes, E., Rudelson, M., Tao, T., & Vershynin, R. (2005). Error correction via linear programming. 46th Annual IEEE Symposium on Foundations of Computer Science (FOCS'05). https://doi.org/10.1109/sfcs.2005.5464411
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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
