Binary sparse phase retrieval via simulated annealing
type: Item
instance of: scholarly article
title: Binary sparse phase retrieval via simulated annealing
zbMATH Open document ID: 1400.94062
DOI: 10.1155/2016/8257612
author: Wei Peng
author: Hongxia Wang
published in: Mathematical Problems in Engineering
publication date: 2018-10-12T00:00:00Z
review text: Summary: This paper presents the Simulated Annealing Sparse PhAse Recovery (SASPAR) algorithm for reconstructing sparse binary signals from their phaseless magnitudes of the Fourier transform. The greedy strategy version is also proposed for a comparison, which is a parameter-free algorithm. Sufficient numeric simulations indicate that our method is quite effective and suggest the binary model is robust. The SASPAR algorithm seems competitive to the existing methods for its efficiency and high recovery rate even with fewer Fourier measurements.
Mathematics Subject Classification ID: 94A12
Mathematics Subject Classification ID: 42A38
Mathematics Subject Classification ID: 90C09
Mathematics Subject Classification ID: 90C59
zbMATH DE Number: 6953634
Wikidata QID: Q59140898
describes a project that uses: PhaseLift
describes a project that uses: Wirtinger Flow
describes a project that uses: GESPAR
MaRDI profile type: Publication
full work available at URL: https://doi.org/10.1155/2016/8257612
OpenAlex ID: W2412427174
cites work: Phase retrieval via matrix completion
cites work: Phase Retrieval via Wirtinger Flow: Theory and Algorithms
cites work: Compressive Phase Retrieval via Generalized Approximate Message Passing
cites work: GESPAR: Efficient Phase Retrieval of Sparse Signals
cites work: Q2743942
cites work: A comparison of simulated annealing cooling strategies
cites work: Q4739657
description: scientific article; zbMATH DE number 6953634