Noise folding in completely perturbed compressed sensing

DOI10.1155/2016/5094239zbMath1435.94100OpenAlexW2319648198WikidataQ59125208 ScholiaQ59125208MaRDI QIDQ670261

Jing Yuan, Limin Zhou, Xin-Xin Niu

Publication date: 18 March 2019

Published in: Journal of Applied Mathematics (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1155/2016/5094239

Mathematics Subject Classification ID

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

Uses Software

• CoSaMP

Cites Work

• A mathematical introduction to compressive sensing
• CoSaMP: Iterative signal recovery from incomplete and inaccurate samples
• Deterministic Construction of Compressed Sensing Matrices via Algebraic Curves
• Recovery of sparse signals using OMP and its variants: convergence analysis based on RIP
• Robust uncertainty principles: exact signal reconstruction from highly incomplete frequency information
• Decoding by Linear Programming
• Stable recovery of sparse overcomplete representations in the presence of noise
• Signal Recovery From Random Measurements Via Orthogonal Matching Pursuit
• An Iterative Bayesian Algorithm for Sparse Component Analysis in Presence of Noise
• Orthogonal Matching Pursuit: A Brownian Motion Analysis
• Perturbation Analysis of Orthogonal Matching Pursuit
• A Remark on the Restricted Isometry Property in Orthogonal Matching Pursuit
• New Bounds for Restricted Isometry Constants
• Analysis of Orthogonal Matching Pursuit Using the Restricted Isometry Property
• Sparse Bayesian Learning for Basis Selection
• Stable signal recovery from incomplete and inaccurate measurements
• Compressed sensing

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