Approximate message-passing with spatially coupled structured operators, with applications to compressed sensing and sparse superposition codes

DOI10.1088/1742-5468/2015/05/P05013zbMath1460.94032arXiv1312.1740OpenAlexW2129857026WikidataQ59460056 ScholiaQ59460056MaRDI QIDQ3302242

Jean Barbier, Florent Krzakala, Christophe Schülke

Publication date: 11 August 2020

Published in: Journal of Statistical Mechanics: Theory and Experiment (Search for Journal in Brave)

Full work available at URL: https://arxiv.org/abs/1312.1740

zbMATH Keywords

message-passing systemsHadamard operatorFourier operator

Mathematics Subject Classification ID

Signal theory (characterization, reconstruction, filtering, etc.) (94A12) Decoding (94B35) Communication theory (94A05) Source coding (94A29)

Related Items (1)

Blind sensor calibration using approximate message passing

Cites Work

• Robust uncertainty principles: exact signal reconstruction from highly incomplete frequency information
• Information, Physics, and Computation
• State evolution for general approximate message passing algorithms, with applications to spatial coupling
• The Dynamics of Message Passing on Dense Graphs, with Applications to Compressed Sensing
• Threshold Saturation via Spatial Coupling: Why Convolutional LDPC Ensembles Perform So Well over the BEC
• Fast Sparse Superposition Codes Have Near Exponential Error Probability for <formula formulatype="inline"><tex Notation="TeX">$R&lt;{\cal C}$</tex></formula>
• Information-Theoretically Optimal Compressed Sensing via Spatial Coupling and Approximate Message Passing
• Asymptotic Analysis of Complex LASSO via Complex Approximate Message Passing (CAMP)
• Compressed sensing

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