Relevant bibliographies by topics / Compressive phase retrieval

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  1. Journal articles

Academic literature on the topic 'Compressive phase retrieval'

Author: Grafiati
Published: 6 September 2023

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Journal articles on the topic "Compressive phase retrieval"

1

Li, Yi, and Vasileios Nakos. "Sublinear-Time Algorithms for Compressive Phase Retrieval." IEEE Transactions on Information Theory 66, no. 11 (2020): 7302–10. http://dx.doi.org/10.1109/tit.2020.3020701.

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2

Zhang, Liang, Gang Wang, Georgios B. Giannakis, and Jie Chen. "Compressive Phase Retrieval via Reweighted Amplitude Flow." IEEE Transactions on Signal Processing 66, no. 19 (2018): 5029–40. http://dx.doi.org/10.1109/tsp.2018.2862395.

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3

Schniter, Philip, and Sundeep Rangan. "Compressive Phase Retrieval via Generalized Approximate Message Passing." IEEE Transactions on Signal Processing 63, no. 4 (2015): 1043–55. http://dx.doi.org/10.1109/tsp.2014.2386294.

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4

Peng, Tong, Runze Li, Junwei Min, et al. "Quantitative Phase Retrieval Through Scattering Medium via Compressive Sensing." IEEE Photonics Journal 14, no. 1 (2022): 1–8. http://dx.doi.org/10.1109/jphot.2021.3136509.

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5

Di, Hong, and Xin Zhang. "Compressive image encryption with customized key based on phase retrieval." Optical Engineering 56, no. 2 (2017): 023103. http://dx.doi.org/10.1117/1.oe.56.2.023103.

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6

Jerez, Andres, Samuel Pinilla, and Henry Arguello. "Fast Target Detection via Template Matching in Compressive Phase Retrieval." IEEE Transactions on Computational Imaging 6 (2020): 934–44. http://dx.doi.org/10.1109/tci.2020.2995999.

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7

Ohlsson, Henrik, Allen Y. Yang, Roy Dong, and S. Shankar Sastry. "Compressive Phase Retrieval From Squared Output Measurements Via Semidefinite Programming*." IFAC Proceedings Volumes 45, no. 16 (2012): 89–94. http://dx.doi.org/10.3182/20120711-3-be-2027.00415.

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8

Li, Yingying, Jinchuan Zhou, Zhongfeng Sun, and Jingyong Tang. "Heavy-Ball-Based Hard Thresholding Pursuit for Sparse Phase Retrieval Problems." Mathematics 11, no. 12 (2023): 2744. http://dx.doi.org/10.3390/math11122744.

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Abstract:
We introduce a novel iterative algorithm, termed the Heavy-Ball-Based Hard Thresholding Pursuit for sparse phase retrieval problem (SPR-HBHTP), to reconstruct a sparse signal from a small number of magnitude-only measurements. Our algorithm is obtained via a natural combination of the Hard Thresholding Pursuit for sparse phase retrieval (SPR-HTP) and the classical Heavy-Ball (HB) acceleration method. The robustness and convergence for the proposed algorithm were established with the help of the restricted isometry property. Furthermore, we prove that our algorithm can exactly recover a sparse signal with overwhelming probability in finite steps whenever the initialization is in the neighborhood of the underlying sparse signal, provided that the measurement is accurate. Extensive numerical tests show that SPR-HBHTP has a markedly improved recovery performance and runtime compared to existing alternatives, such as the Hard Thresholding Pursuit for sparse phase retrieval problem (SPR-HTP), the SPARse Truncated Amplitude Flow (SPARTA), and Compressive Phase Retrieval with Alternating Minimization (CoPRAM).
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9

Pedarsani, Ramtin, Dong Yin, Kangwook Lee, and Kannan Ramchandran. "PhaseCode: Fast and Efficient Compressive Phase Retrieval Based on Sparse-Graph Codes." IEEE Transactions on Information Theory 63, no. 6 (2017): 3663–91. http://dx.doi.org/10.1109/tit.2017.2693287.

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10

Hu, Chen, Xiaodong Wang, Linglong Dai, and Junjie Ma. "Partially Coherent Compressive Phase Retrieval for Millimeter-Wave Massive MIMO Channel Estimation." IEEE Transactions on Signal Processing 68 (2020): 1673–87. http://dx.doi.org/10.1109/tsp.2020.2975914.

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