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In this paper, we focus on the approximation of smooth functions $f: [-\pi, \pi] \rightarrow \mathbb{C}$, up to an unresolvable global phase ambiguity, from a finite set of Short Time Fourier Transform (STFT) magnitude (i.e., spectrogram)…

Numerical Analysis · Mathematics 2021-06-07 Mark Iwen , Michael Perlmutter , Nada Sissouno , Aditya Viswanathan

The problem of phase retrieval is revisited and studied from a fresh perspective. In particular, we establish a connection between the phase retrieval problem and the sensor network localization problem, which allows us to utilize the vast…

Optimization and Control · Mathematics 2018-03-22 Sherry Xue-Ying Ni , Man-Chung Yue , Kam-Fung Cheung , Anthony Man-Cho So

Even though image signals are typically defined on a regular two-dimensional grid, there also exist many scenarios where this is not the case and the amplitude of the image signal only is available for a non-regular subset of pixel…

Image and Video Processing · Electrical Eng. & Systems 2022-04-28 Jürgen Seiler , Markus Jonscher , Michael Schöberl , André Kaup

In this paper, we show that sparse signals f representable as a linear combination of a finite number N of spikes at arbitrary real locations or as a finite linear combination of B-splines of order m with arbitrary real knots can be almost…

Numerical Analysis · Mathematics 2020-02-19 Robert Beinert , Gerlind Plonka

The aim of this paper is to build up the theoretical framework for the recovery of sparse signals from the magnitude of the measurement. We first investigate the minimal number of measurements for the success of the recovery of sparse…

Information Theory · Computer Science 2013-10-07 Yang Wang , Zhiqiang Xu

A novel phase retrieval method, motivated by ptychographic imaging, is proposed for the approximate recovery of a compactly supported specimen function $f:\mathbb{R}\rightarrow\mathbb{C}$ from its continuous short time Fourier transform…

Numerical Analysis · Mathematics 2017-06-07 Sami Merhi , Aditya Viswanathan , Mark Iwen

The recent introduction of coherent optical communications has created a compelling need for ultra-fast phase-sensitive measurement techniques operating at milliwatt peak power levels and in time scales ranging from sub-picoseconds to…

Phase retrieval (PR) is an inverse problem about recovering a signal from phaseless linear measurements. This problem can be effectively solved by minimizing a nonconvex amplitude-based loss function. However, this loss function is…

Signal Processing · Electrical Eng. & Systems 2020-07-24 Q. Luo , H. Wang

Phase retrieval is the nonlinear inverse problem of recovering a true signal from its Fourier magnitude measurements. It arises in many applications such as astronomical imaging, X-Ray crystallography, microscopy, and more. The problem is…

Computer Vision and Pattern Recognition · Computer Science 2023-05-11 Rohun Agrawal , Oscar Leong

We consider the geometry associated to the ambiguities of the one-dimensional Fourier phase retrieval problem for vectors in ${\mathbb C}^{N+1}$. Our first result states that the space of signals has a finite covering (which we call the…

Functional Analysis · Mathematics 2019-09-24 Dan Edidin

We consider the problem of reconstructing two signals from the autocorrelation and cross-correlation measurements. This inverse problem is a fundamental one in signal processing, and arises in many applications, including phase retrieval…

Information Theory · Computer Science 2016-10-11 Kishore Jaganathan , Babak Hassibi

We consider the recovery of a (real- or complex-valued) signal from magnitude-only measurements, known as phase retrieval. We formulate phase retrieval as a convex optimization problem, which we call PhaseMax. Unlike other convex methods…

Information Theory · Computer Science 2018-01-31 Tom Goldstein , Christoph Studer

In the context of the phase retrieval problem, it is known that certain natural classes of measurements, such as Fourier measurements and random Bernoulli measurements, do not lead to the unique reconstruction of all possible signals, even…

Information Theory · Computer Science 2018-03-07 Felix Krahmer , Yi-Kai Liu

In this paper, we provide a Graph Fourier Transform based approach to downsample signals on graphs. For bandlimited signals on a graph, a test is provided to identify whether signal reconstruction is possible from the given downsampled…

Other Statistics · Statistics 2016-12-23 Nileshkumar Vaishnav , Aditya Tatu

Affine phase retrieval is the problem of recovering signals from the magnitude-only measurements with a priori information. In this paper, we use the $\ell_1$ minimization to exploit the sparsity of signals for affine phase retrieval,…

Information Theory · Computer Science 2022-09-20 Meng Huang , Shixiang Sun , Zhiqiang Xu

In this study, we propose a generalized turbo signal recovery algorithm to estimate a signal from quantized measurements, in which the sensing matrix is a row-orthogonal matrix, such as the partial discrete Fourier transform matrix. The…

Information Theory · Computer Science 2016-11-17 Ting Liu , Chao-Kai Wen , Shi Jin , Xiaohu You

We introduce a framework for the reconstruction of the amplitude, phase and polarisation of an optical vector-field using calibration measurements acquired by an imaging device with an unknown linear transformation. By incorporating…

Measurements achieved with ptychographic imaging are a special case of diffraction measurements. They are generated by illuminating small parts of a sample with, e.g., a focused X-ray beam. By shifting the sample, a set of far-field…

In this work, we present some new results for compressed sensing and phase retrieval. For compressed sensing, it is shown that if the unknown $n$-dimensional vector can be expressed as a linear combination of $s$ unknown Vandermonde vectors…

Information Theory · Computer Science 2024-02-16 Dzevdan Kapetanovic

Phase retrieval problem has been studied in various applications. It is an inverse problem without the standard uniqueness guarantee. To make complete theoretical analyses and devise efficient algorithms to recover the signal is…

Information Theory · Computer Science 2019-05-22 Ziyang Yuan , Hongxia Wang
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