PhaseLift: Exact and Stable Signal Recovery from Magnitude Measurements via Convex Programming

被引:824
作者
Candes, Emmanuel J. [1 ]
Strohmer, Thomas [2 ]
Voroninski, Vladislav [3 ]
机构
[1] Stanford Univ, Dept Math & Stat, Stanford, CA 94305 USA
[2] Univ Calif Davis, Dept Math, Davis, CA 95616 USA
[3] Univ Calif Berkeley, Dept Math, Berkeley, CA 94720 USA
基金
美国国家科学基金会;
关键词
RETRIEVAL;
D O I
10.1002/cpa.21432
中图分类号
O29 [应用数学];
学科分类号
070104 ;
摘要
Suppose we wish to recover a signal x epsilon C-n from m intensity measurements of the form vertical bar < x, z(i)>vertical bar(2), i = 1, 2,..., m; that is, from data in which phase information is missing. We prove that if the vectors z(i) are sampled independently and uniformly at random on the unit sphere, then the signal x can be recovered exactly (up to a global phase factor) by solving a convenient semidefinite program-a trace-norm minimization problem; this holds with large probability provided that m is on the order of n log n, and without any assumption about the signal whatsoever. This novel result demonstrates that in some instances, the combinatorial phase retrieval problem can be solved by convex programming techniques. Finally, we also prove that our methodology is robust vis-a-vis additive noise. (c) 2012 Wiley Periodicals, Inc.
引用
收藏
页码:1241 / 1274
页数:34
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