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Title: Sublinear-time algorithms for compressive phase retrieval
Authors: Li, Yi
Nakos, Vasileios
Keywords: Engineering::Computer science and engineering
Issue Date: 2020
Source: Li, Y. & Nakos, V. (2020). Sublinear-time algorithms for compressive phase retrieval. IEEE Transactions On Information Theory, 66(11), 7302-7310.
Journal: IEEE Transactions on Information Theory
Abstract: In the problem of compressed phase retrieval, the goal is to reconstruct a sparse or approximately k-sparse vector x in C n given access to y= |φ x|, where |v| denotes the vector obtained from taking the absolute value of v inCn coordinate-wise. In this paper we present sublinear-time algorithms for a few for-each variants of the compressive phase retrieval problem which are akin to the variants considered for the classical compressive sensing problem in theoretical computer science. Our algorithms use pure combinatorial techniques and near-optimal number of measurements.
ISSN: 0018-9448
DOI: 10.1109/TIT.2020.3020701
Schools: School of Physical and Mathematical Sciences 
Rights: © 2020 IEEE. All rights reserved.
Fulltext Permission: none
Fulltext Availability: No Fulltext
Appears in Collections:SPMS Journal Articles

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