Sparse recovery under nonnegativity and sum-to-one constraints
Sparse recovery under nonnegativity and sum-to-one constraints is a special form of the
linear regression problem, where the solution is required to simultaneously satisfy sparsity …
linear regression problem, where the solution is required to simultaneously satisfy sparsity …
Robust sparse representation based on fitting error decomposition
Sparse representation (SR) of a signal aims at finding the minimum number of atoms for its
representation. In several practical scenarios, the signal is vulnerable to outliers and thus …
representation. In several practical scenarios, the signal is vulnerable to outliers and thus …
Enhanced One-Bit SAR Imaging Method Using Two-Level Structured Sparsity to Mitigate Adverse Effects of Sign Flips
S Ge, N Jiang, D Feng, S Song, J Wang… - … on Geoscience and …, 2024 - ieeexplore.ieee.org
One-bit synthetic aperture radar (SAR) imaging technology has garnered significant
attention due to its ability to substantially reduce system complexity and data storage …
attention due to its ability to substantially reduce system complexity and data storage …
One-Bit Underdetermined DOA Estimation with Sparse Arrays via Structured Covariance Reconstruction
Recently, one-bit direction of arrival (DOA) estimation has received significant attention due
to its low cost and low implementation complexity, while still achieving high accuracy without …
to its low cost and low implementation complexity, while still achieving high accuracy without …