Large-Scale Phase Retrieval via Stochastic Reweighted Amplitude Flow

Phase retrieval, recovering a signal from phaseless measurements, is generally considered to be an NP-hard problem. This paper adopts an amplitude-based nonconvex optimization cost function to develop a new stochastic gradient algorithm, named stochastic reweighted phase retrieval (SRPR). SRPR is a...

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Veröffentlicht in:	KSII transactions on Internet and information systems 2020-11, Vol.14 (11), p.4355-4371
Hauptverfasser:	Xiao, Zhuolei, Zhang, Yerong, Yang, Jie
Format:	Artikel
Sprache:	kor
Schlagworte:	Nonconvex optimization Phase retrieval sample stochastic variance reduction stochastic reweighted gradient iteration
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