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We consider a phase retrieval problem, where we want to reconstruct a $n$-dimensional vector from its phaseless scalar products with $m$ sensing vectors.
A practical algorithm for the determination of phase from image and diffraction plane pictures
R. Gerchberg and W. Saxton · 1972
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Phase retrieval algorithms: a comparison
J. R. Fienup · 1982
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Local operator theory, random matrices and Banach spaces
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Local linear convergence for alternating and averaged nonconvex projections
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Array imaging using intensity-only measurements
A. Chai, M. Moscoso, and G. Papanicolaou · 2011
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Introduction to the non-asymptotic analysis of random matrices
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Phase retrieval using alternating minimization
P. Netrapalli, P. Jain, and S. Sanghavi · 2013
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Solving quadratic equations via phaselift when there are about as many equations as unknowns
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Phase retrieval from coded diffraction patterns
E. J. Candès, X. Li, and M. Soltanolkotabi · 2015
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Phase retrieval via wirtinger flow: theory and algorithms
E. J. Candès, X. Li, and M. Soltanolkotabi · 2015
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Solving random quadratic systems of equations is nearly as easy as solving linear systems
Y. Chen and E. J. Candès · 2015
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The local convexity of solving systems of quadratic equations
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P. Chen, A. Fannjiang, and G.-R. Liu · 2016
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Gauss-Newton method for phase retrieval
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Transversality and alternating projections for nonconvex sets
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