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- W3005192067 abstract "We consider the phase retrieval problem, where the goal is to reconstruct an n-dimensional complex vector from its phaseless scalar products with m sensing vectors, independently sampled from complex normal distributions. We show that, if m ≥ Mn <sup xmlns:mml=http://www.w3.org/1998/Math/MathML xmlns:xlink=http://www.w3.org/1999/xlink>3/2</sup> log <sup xmlns:mml=http://www.w3.org/1998/Math/MathML xmlns:xlink=http://www.w3.org/1999/xlink>7/2</sup> n for some M > 0, then the classical algorithm of alternating minimization with random initialization succeeds with high probability as n, m → ∞. This is a step toward proving the conjecture in, which conjectures that the algorithm succeeds when m = O(n). The analysis depends on an approach that enables the decoupling of the dependency between the algorithmic iterates and the sensing vectors." @default.
- W3005192067 created "2020-02-14" @default.
- W3005192067 creator A5033785543 @default.
- W3005192067 date "2020-07-01" @default.
- W3005192067 modified "2023-09-29" @default.
- W3005192067 title "Phase Retrieval by Alternating Minimization With Random Initialization" @default.
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- W3005192067 doi "https://doi.org/10.1109/tit.2020.2971211" @default.
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