Sublinear-time algorithms for compressive phase retrieval

Sublinear-time algorithms for compressive phase retrieval

In the compressive phase retrieval problem, the goal is to reconstruct a sparse or approximately k-sparse vector x ∈ R n given access to y = |Φ x |, where |v| denotes the vector obtained from taking the absolute value of v ∈ R n coordinatewise. In this paper we present sublinear-time algorithms for...

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Main Authors: Li, Yi, Nakos, Vasileios
Other Authors: School of Physical and Mathematical Sciences
Format: Conference or Workshop Item
Language:English
Published: 2020
Subjects:
Science::Mathematics
Decoding
Signal Processing Algorithms
Online Access:https://hdl.handle.net/10356/142571
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Institution: Nanyang Technological University
Language: English
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spelling sg-ntu-dr.10356-1425712020-06-24T07:56:12Z Sublinear-time algorithms for compressive phase retrieval Li, Yi Nakos, Vasileios School of Physical and Mathematical Sciences 2018 IEEE International Symposium on Information Theory (ISIT 2018) Science::Mathematics Decoding Signal Processing Algorithms In the compressive phase retrieval problem, the goal is to reconstruct a sparse or approximately k-sparse vector x ∈ R n given access to y = |Φ x |, where |v| denotes the vector obtained from taking the absolute value of v ∈ R n coordinatewise. In this paper we present sublinear-time algorithms for different variants of the compressive phase retrieval problem which are akin to the variants of the classical compressive sensing problem considered in theoretical computer science. Our algorithms use pure combinatorial techniques and achieve almost optimal number of measurements. 2020-06-24T07:56:12Z 2020-06-24T07:56:12Z 2018 Conference Paper Li, Y., & Nakos, V. (2018). Sublinear-time algorithms for compressive phase retrieval. Proceedings of 2018 IEEE International Symposium on Information Theory (ISIT 2018), 2301-2305. doi:10.1109/ISIT.2018.8437599 978-1-5386-4102-6 https://hdl.handle.net/10356/142571 10.1109/ISIT.2018.8437599 2-s2.0-85052485587 2301 2305 en © 2018 IEEE. All rights reserved.
institution Nanyang Technological University
building NTU Library
country Singapore
collection DR-NTU
language English
topic Science::Mathematics
Decoding
Signal Processing Algorithms
spellingShingle Science::Mathematics
Decoding
Signal Processing Algorithms
Li, Yi
Nakos, Vasileios
Sublinear-time algorithms for compressive phase retrieval
description In the compressive phase retrieval problem, the goal is to reconstruct a sparse or approximately k-sparse vector x ∈ R n given access to y = |Φ x |, where |v| denotes the vector obtained from taking the absolute value of v ∈ R n coordinatewise. In this paper we present sublinear-time algorithms for different variants of the compressive phase retrieval problem which are akin to the variants of the classical compressive sensing problem considered in theoretical computer science. Our algorithms use pure combinatorial techniques and achieve almost optimal number of measurements.
author2 School of Physical and Mathematical Sciences
author_facet School of Physical and Mathematical Sciences
Li, Yi
Nakos, Vasileios
format Conference or Workshop Item
author Li, Yi
Nakos, Vasileios
author_sort Li, Yi
title Sublinear-time algorithms for compressive phase retrieval
title_short Sublinear-time algorithms for compressive phase retrieval
title_full Sublinear-time algorithms for compressive phase retrieval
title_fullStr Sublinear-time algorithms for compressive phase retrieval
title_full_unstemmed Sublinear-time algorithms for compressive phase retrieval
title_sort sublinear-time algorithms for compressive phase retrieval
publishDate 2020
url https://hdl.handle.net/10356/142571
_version_ 1681058511882027008

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