Single snapshot DOA estimation by minimizing the fraction function in sparse recovery
From MaRDI portal
Publication:2007122
DOI10.1155/2020/6163529zbMath1459.94048OpenAlexW3080457702MaRDI QIDQ2007122
Publication date: 12 October 2020
Published in: Mathematical Problems in Engineering (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1155/2020/6163529
Ill-posedness and regularization problems in numerical linear algebra (65F22) Applications of mathematical programming (90C90) Nonconvex programming, global optimization (90C26) Signal theory (characterization, reconstruction, filtering, etc.) (94A12)
Cites Work
- A mathematical introduction to compressive sensing
- Sparse frame DOA estimations via a rank-one correlation model for low SNR and limited snapshots
- Sharp RIP bound for sparse signal and low-rank matrix recovery
- $NP/CMP$ Equivalence: A Phenomenon Hidden Among Sparsity Models $l_{0}$ Minimization and $l_{p}$ Minimization for Information Processing
- Bayesian Beamforming for DOA Uncertainty: Theory and Implementation
This page was built for publication: Single snapshot DOA estimation by minimizing the fraction function in sparse recovery
