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Related papers: Phase Retrieval From Binary Measurements

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We address the problem of blind gain and phase calibration of a sensor array from ambient noise. The key motivation is to ease the calibration process by avoiding a complex procedure setup. We show that computing the sample covariance…

Instrumentation and Detectors · Physics 2023-03-22 Charles Vanwynsberghe , Simon Bouley , Jérôme Antoni

In this work we develop an algorithm for signal reconstruction from the magnitude of its Fourier transform in a situation where some (non-zero) parts of the sought signal are known. Although our method does not assume that the known part…

Optics · Physics 2012-03-06 Eliyahu Osherovich , Michael Zibulevsky , Irad Yavneh

The Compressive Sensing (CS) framework aims to ease the burden on analog-to-digital converters (ADCs) by reducing the sampling rate required to acquire and stably recover sparse signals. Practical ADCs not only sample but also quantize each…

Information Theory · Computer Science 2015-11-04 Laurent Jacques , Jason N. Laska , Petros T. Boufounos , Richard G. Baraniuk

To achieve the joint active and passive beamforming gains in the reconfigurable intelligent surface assisted millimeter wave system, the reflected cascade channel needs to be accurately estimated. Many strategies have been proposed in the…

Information Theory · Computer Science 2021-09-22 Yiming Liu , Erwu Liu , Rui Wang , Zhu Han , Binyu Lu

Quantized compressive sensing (QCS) deals with the problem of representing compressive signal measurements with finite precision representation, i.e., a mandatory process in any practical sensor design. To characterize the signal…

Information Theory · Computer Science 2018-05-14 Chunlei Xu , Vincent Schellekens , Laurent Jacques

We propose a novel soft-aided iterative decoding algorithm for product codes (PCs). The proposed algorithm, named iterative bounded distance decoding with combined reliability (iBDD-CR), enhances the conventional iterative bounded distance…

Information Theory · Computer Science 2021-09-08 Alireza Sheikh , Alexandre Graell i Amat , Gianluigi Liva , Alex Alvarado

Recent progress in robust statistical learning has mainly tackled convex problems, like mean estimation or linear regression, with non-convex challenges receiving less attention. Phase retrieval exemplifies such a non-convex problem,…

Machine Learning · Statistics 2024-10-15 Alex Buna , Patrick Rebeschini

Image signals typically are defined on a rectangular two-dimensional grid. However, there exist scenarios where this is not fulfilled and where the image information only is available for a non-regular subset of pixel position. For…

Image and Video Processing · Electrical Eng. & Systems 2022-07-15 Jürgen Seiler , André Kaup

This paper discusses the noisy phase retrieval problem: recovering a complex image signal with independent noise from quadratic measurements. Inspired by the dark fringes shown in the measured images of the array detector, a novel phase…

Computer Vision and Pattern Recognition · Computer Science 2022-04-14 Wen-Kai Yu , An-Dong Xiong , Xu-Ri Yao , Guang-Jie Zhai , Qing Zhao

We address the problem of recovering a signal (up to global phase) from its short-time Fourier transform (STFT) magnitude measurements. This problem arises in several applications, including optical imaging and speech processing. In this…

Information Theory · Computer Science 2015-10-06 Tamir Bendory , Yonina C. Eldar

Phase retrieval is an important problem with significant physical and industrial applications. In this paper, we consider the case where the magnitude of the measurement of an underlying signal is corrupted by Gaussian noise. We introduce a…

Optimization and Control · Mathematics 2022-05-03 Jianwei Niu , Hok Shing Wong , Tieyong Zeng

In phase retrieval, the goal is to recover a signal $\mathbf{x}\in\mathbb{C}^N$ from the magnitudes of linear measurements $\mathbf{Ax}\in\mathbb{C}^M$. While recent theory has established that $M\approx 4N$ intensity measurements are…

Information Theory · Computer Science 2015-06-19 Philip Schniter , Sundeep Rangan

This paper studies the problem of recovering a signal from one-bit compressed sensing measurements under a manifold model; that is, assuming that the signal lies on or near a manifold of low intrinsic dimension. We provide a convex recovery…

Information Theory · Computer Science 2020-07-24 Mark A. Iwen , Felix Krahmer , Sara Krause-Solberg , Johannes Maly

This paper proposes a new framework to regularize the highly ill-posed and non-linear phase retrieval problem through deep generative priors using simple gradient descent algorithm. We experimentally show effectiveness of proposed algorithm…

Machine Learning · Computer Science 2018-08-20 Fahad Shamshad , Ali Ahmed

The compressive sensing (CS) and 1-bit CS demonstrate superior efficiency in signal acquisition and resource conservation, while 1-bit CS achieves maximum resource efficiency through sign-only measurements. With the emergence of massive…

Methodology · Statistics 2025-05-06 Erbo Li , Qi Qin , Yifan Sun , Liping Zhu

In this paper we study the quantization stage that is implicit in any compressed sensing signal acquisition paradigm. We propose using Sigma-Delta quantization and a subsequent reconstruction scheme based on convex optimization. We prove…

Information Theory · Computer Science 2015-04-02 Rayan Saab , Rongrong Wang , Ozgur Yilmaz

We consider the robust phase retrieval problem of recovering the unknown signal from the magnitude-only measurements, where the measurements can be contaminated by both sparse arbitrary corruption and bounded random noise. We propose a new…

Machine Learning · Statistics 2018-01-08 Jinghui Chen , Lingxiao Wang , Xiao Zhang , Quanquan Gu

Ptychography has risen as a reference X-ray imaging technique: it achieves resolutions of one billionth of a meter, macroscopic field of view, or the capability to retrieve chemical or magnetic contrast, among other features. A…

Optimization and Control · Mathematics 2019-06-10 Huibin Chang , Pable Enfedaque , Stefano Marchesini

We study the problem of recovering the phase from magnitude measurements; specifically, we wish to reconstruct a complex-valued signal x of C^n about which we have phaseless samples of the form y_r = |< a_r,x >|^2, r = 1,2,...,m (knowledge…

Information Theory · Computer Science 2016-11-17 Emmanuel Candes , Xiaodong Li , Mahdi Soltanolkotabi

There have been a number of studies on sparse signal recovery from one-bit quantized measurements. Nevertheless, little attention has been paid to the choice of the quantization thresholds and its impact on the signal recovery performance.…

Information Theory · Computer Science 2013-05-21 Jun Fang , Yanning Shen , Hongbin Li