Signal Space CoSaMP for Sparse Recovery With Redundant Dictionaries

DOI10.1109/TIT.2013.2273491zbMath1364.94119arXiv1208.0353OpenAlexW2077520262MaRDI QIDQ5346325

Deanna Needell, Michael B. Wakin, Mark A. Davenport

Publication date: 8 June 2017

Published in: IEEE Transactions on Information Theory (Search for Journal in Brave)

Full work available at URL: https://arxiv.org/abs/1208.0353

Mathematics Subject Classification ID

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

Related Items

A geometrical stability condition for compressed sensing, Sparsity Based Methods for Overparameterized Variational Problems, Compressive Sensing with Redundant Dictionaries and Structured Measurements, Generalizing CoSaMP to signals from a union of low dimensional linear subspaces, Arbitrary block-sparse signal reconstruction based on incomplete single measurement vector, Sampling rates for \(\ell^1\)-synthesis, Sampling in the analysis transform domain, Flavors of Compressive Sensing, Estimation in High Dimensions: A Geometric Perspective, Dictionary-sparse recovery via thresholding-based algorithms, Data-driven algorithm selection and tuning in optimization and signal processing, Greedy approximate projection for magnetic resonance fingerprinting with partial volumes, Preserving injectivity under subgaussian mappings and its application to compressed sensing, Near oracle performance and block analysis of signal space greedy methods, Greedy signal space methods for incoherence and beyond

Uses Software

• CoSaMP