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Compressed sensing for phase retrieval

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Please use this identifier to cite or link to this item:http://hdl.handle.net/2115/49430

Title: Compressed sensing for phase retrieval
Authors: Newton, Marcus C. Browse this author →KAKEN DB
Issue Date: May-2012
Publisher: American Physical Society
Journal Title: Physical Review E
Volume: 85
Issue: 5
Start Page: 056706
Publisher DOI: 10.1103/PhysRevE.85.056706
Abstract: To date there are several iterative techniques that enjoy moderate success when reconstructing phase information, where only intensity measurements are made. There remains, however, a number of cases in which conventional approaches are unsuccessful. In the last decade, the theory of compressed sensing has emerged and provides a route to solving convex optimisation problems exactly via ℓ1-norm minimization. Here the application of compressed sensing to phase retrieval in a nonconvex setting is reported. An algorithm is presented that applies reweighted ℓ1-norm minimization to yield accurate reconstruction where conventional methods fail.
Rights: ©2012 American Physical Society
Type: article
URI: http://hdl.handle.net/2115/49430
Appears in Collections:電子科学研究所 (Research Institute for Electronic Science) > 雑誌発表論文等 (Peer-reviewed Journal Articles, etc)

Submitter: Newton Marcus Christian

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