BranchHull: convex bilinear inversion from the entrywise product of signals with known signs

DOI10.1016/j.acha.2019.03.002zbMath1448.94042arXiv1702.04342OpenAlexW2594807468MaRDI QIDQ778035

D. Kharzeev

Publication date: 30 June 2020

Published in: Applied and Computational Harmonic Analysis (Search for Journal in Brave)

Full work available at URL: https://arxiv.org/abs/1702.04342

zbMATH Keywords

blind source separationconvex programmingblind deconvolutionBranchHull

Mathematics Subject Classification ID

Convex programming (90C25) Signal theory (characterization, reconstruction, filtering, etc.) (94A12)

Related Items (4)

Simultaneous Phase Retrieval and Blind Deconvolution via Convex Programming ⋮ Convex and Nonconvex Optimization Are Both Minimax-Optimal for Noisy Blind Deconvolution Under Random Designs ⋮ Estimation from nonlinear observations via convex programming with application to bilinear regression ⋮ BranchHull

Uses Software

• PhaseMax
• Wirtinger Flow

Cites Work

• Unnamed Item
• A global optimization algorithm for linear fractional and bilinear programs
• Phase Retrieval via Wirtinger Flow: Theory and Algorithms
• Blind Deconvolution Using Convex Programming
• Self-calibration and biconvex compressive sensing
• A Problem in Geometric Probability.
• Computability of global solutions to factorable nonconvex programs: Part I — Convex underestimating problems
• Solving Systems of Random Quadratic Equations via Truncated Amplitude Flow
• PhaseMax: Convex Phase Retrieval via Basis Pursuit
• Leveraging Diversity and Sparsity in Blind Deconvolution

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