The DOI matches its Crossref record; 68 of the 68 references it cites were found in a registry or an index.
Compressive Sensing in Electromagnetics - A Review
Abstract
Several problems arising in electromagnetics can be directly formulated or suitably recast for an effective solution within the compressive sensing (CS) framework. This has motivated a great interest in developing and applying CS methodologies to several conventional and innovative electromagnetic scenarios. This work is aimed at presenting, to the best of the authors' knowledge, a review of the state-of-the-art and most recent advances of CS formulations and related methods as applied to electromagnetics. Toward this end, a wide set of applicative scenarios comprising the diagnosis and synthesis of antenna arrays, the estimation of directions of arrival, and the solution of inverse scattering and radar imaging problems are reviewed. Current challenges and trends in the application of CS to the solution of traditional and new electromagnetic problems are also discussed.
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cites
Regression shrinkage and selection via the lasso
Tibshirani, R. (1996) · Journal of the Royal Statistical Society Series B: Statistical Methodology · doi:10.1111/j.2517-6161.1996.tb02080.x · Cited by 51,482
Candes, E. J., Romberg, J., & Tao, T. (2006) · IEEE Transactions on Information Theory · doi:10.1109/tit.2005.862083 · Cited by 15,639
An Introduction To Compressive Sampling
Candes, E. J., & Wakin, M. B. (2008) · IEEE Signal Processing Magazine · doi:10.1109/msp.2007.914731 · Cited by 10,017
Signal Recovery From Random Measurements Via Orthogonal Matching Pursuit
Tropp, J. A., & Gilbert, A. C. (2007) · IEEE Transactions on Information Theory · doi:10.1109/tit.2007.909108 · Cited by 9,653
Matching pursuits with time-frequency dictionaries
Mallat, S. G., & Zhang, Z. (1993) · IEEE Transactions on Signal Processing · doi:10.1109/78.258082 · Cited by 9,112
Decoding by Linear Programming
Candes, E. J., & Tao, T. (2005) · IEEE Transactions on Information Theory · doi:10.1109/tit.2005.858979 · Cited by 7,121
Enhancing Sparsity by Reweighted ℓ 1 Minimization
Candès, E. J., Wakin, M. B., & Boyd, S. P. (2008) · Journal of Fourier Analysis and Applications · doi:10.1007/s00041-008-9045-x · Cited by 4,863
CoSaMP: Iterative signal recovery from incomplete and inaccurate samples
Needell, D., & Tropp, J. A. (2009) · Applied and Computational Harmonic Analysis · doi:10.1016/j.acha.2008.07.002 · Cited by 4,326
Compressive Sensing [Lecture Notes]
Baraniuk, R. (2007) · IEEE Signal Processing Magazine · doi:10.1109/msp.2007.4286571 · Cited by 4,177
Graph Implementations for Nonsmooth Convex Programs
Grant, M. C., & Boyd, S. P. (2007) · Lecture Notes in Control and Information Sciences · doi:10.1007/978-1-84800-155-8_7 · Cited by 2,666
Metadata
- Authors
- Massa, A., Rocca, P., & Oliveri, G.
- Venue
- IEEE Antennas and Propagation Magazine
- Published
- 2015-02
- Volume
- 57
- Issue
- 1
- Pages
- 224-238
- ISSN
- 1045-9243 (ISSN-L)
- OpenAlex
- W2088213824
- Cited by
- 360
- References
- 68
- FWCI
- 50.58
- Type
- journal article
- Language
- en
- Open access
- closed
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
How to cite
Cite CoChat for the checks on this page, and the paper for its own findings.
- This page
- CoChat. (2026). Citation check: Compressive Sensing in Electromagnetics - A Review. https://app.cochat.ai/papers/10.1109/map.2015.2397092
- The paper
- Massa, A., Rocca, P., & Oliveri, G. (2015). Compressive Sensing in Electromagnetics - A Review. IEEE Antennas and Propagation Magazine. https://doi.org/10.1109/map.2015.2397092
Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
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.
