Compressive sensing in signal processing: algorithms and transform domain formulations
From MaRDI portal
Publication:1793545
DOI10.1155/2016/7616393zbMath1400.94061OpenAlexW2534721159WikidataQ59141192 ScholiaQ59141192MaRDI QIDQ1793545
Irena Orović, Cornel Ioana, Xiumei Li, Vladan Papić, Srdjan S. Stanković
Publication date: 12 October 2018
Published in: Mathematical Problems in Engineering (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1155/2016/7616393
Related Items (4)
Inertial projection and contraction methods for split feasibility problem applied to compressed sensing and image restoration ⋮ Memory-Efficient Structured Convex Optimization via Extreme Point Sampling ⋮ Descent three-term DY-type conjugate gradient methods for constrained monotone equations with application ⋮ JPEG lifting algorithm based on adaptive block compressed sensing
Uses Software
Cites Work
- Unnamed Item
- A mathematical introduction to compressive sensing
- Iterative hard thresholding for compressed sensing
- Iterative thresholding for sparse approximations
- CoSaMP: Iterative signal recovery from incomplete and inaccurate samples
- Compressive sensing approach in the Hermite transform domain
- Robust uncertainty principles: exact signal reconstruction from highly incomplete frequency information
- Decoding by Linear Programming
- Signal Recovery From Random Measurements Via Orthogonal Matching Pursuit
- Structured Compressed Sensing: From Theory to Applications
- Efficient Compression of QRS Complexes Using Hermite Expansion
- Matching pursuits with time-frequency dictionaries
- Sampling Theory
- Sparse Solution of Underdetermined Systems of Linear Equations by Stagewise Orthogonal Matching Pursuit
- Sparsity and incoherence in compressive sampling
- Compressed sensing
This page was built for publication: Compressive sensing in signal processing: algorithms and transform domain formulations