Compressive sensing in signal processing: algorithms and transform domain formulations

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

Mathematics Subject Classification ID

Signal theory (characterization, reconstruction, filtering, etc.) (94A12)

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

• CoSaMP

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

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