標題: Decentralized Expectation Consistent Signal Recovery for Phase Retrieval
作者: Wang, Chang-Jen
Wen, Chao-Kai
Tsai, Shang-Ho
Jin, Shi
電子工程學系及電子研究所
電控工程研究所
Department of Electronics Engineering and Institute of Electronics
Institute of Electrical and Control Engineering
關鍵字: Signal processing algorithms;Transforms;Approximation algorithms;Inference algorithms;Robustness;Bayes methods;Phase measurement;Phase retrieval;Bayes-optimal inference;expectation consistent;decentralized algorithm;distributed processing
公開日期: 1-Jan-2020
摘要: In this study, we present a phase retrieval solution that aims to recover signals from noisy phaseless measurements. A recently proposed scheme known as generalized expectation consistent signal recovery (GEC-SR), has shown better accuracy, speed, and robustness than many existing methods. However, sensing high-resolution images with large transform matrices presents a computational burden for GEC-SR, thereby limiting its applications to areas, such as real-time implementation. Moreover, GEC-SR does not support distributed computing, which is an important requirement to modern computing. To address these issues, we propose a novel decentralized algorithm called & x201C;deGEC-SR & x201D; by leveraging the core framework of GEC-SR. deGEC-SR exhibits excellent performance similar to GEC-SR but runs tens to hundreds of times faster than GEC-SR. We derive the theoretical state evolution for deGEC-SR and demonstrate its accuracy using numerical results. Analysis allows quick generation of performance predictions and enriches our understanding on the proposed algorithm.
URI: http://dx.doi.org/10.1109/TSP.2020.2974711
http://hdl.handle.net/11536/154236
ISSN: 1053-587X
DOI: 10.1109/TSP.2020.2974711
期刊: IEEE TRANSACTIONS ON SIGNAL PROCESSING
Volume: 68
起始頁: 1484
結束頁: 1499
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