Results 11 to 20 of about 173,735 (257)

Sub-Millisecond Phase Retrieval for Phase-Diversity Wavefront Sensor [PDF]

open access: yesSensors, 2020
We propose a convolutional neural network (CNN) based method, namely phase diversity convolutional neural network (PD-CNN) for the speed acceleration of phase-diversity wavefront sensing.
Yu Wu   +3 more
doaj   +2 more sources

The numerics of phase retrieval [PDF]

open access: yesActa Numerica, 2020
Phase retrieval,i.e.the problem of recovering a function from the squared magnitude of its Fourier transform, arises in many applications, such as X-ray crystallography, diffraction imaging, optics, quantum mechanics and astronomy. This problem has confounded engineers, physicists, and mathematicians for many decades. Recently, phase retrieval has seen
Albert Fannjiang, Thomas Strohmer
openaire   +3 more sources

Phase Retrieval with Polarization [PDF]

open access: yesSIAM Journal on Imaging Sciences, 2014
In many areas of imaging science, it is difficult to measure the phase of linear measurements. As such, one often wishes to reconstruct a signal from intensity measurements, that is, perform phase retrieval. In this paper, we provide a novel measurement design which is inspired by interferometry and exploits certain properties of expander graphs.
Boris Alexeev   +3 more
openaire   +2 more sources

Frame Phase-Retrievability and Exact Phase-Retrievable Frames [PDF]

open access: yesJournal of Fourier Analysis and Applications, 2019
An exact phase-retrievable frame $\{f_{i}\}_{i}^{N}$ for an $n$-dimensional Hilbert space is a phase-retrievable frame that fails to be phase-retrievable if any one element is removed from the frame. Such a frame could have different lengths. We shall prove that for the real Hilbert space case, exact phase-retrievable frame of length $N$ exists for ...
Han, Deguang   +3 more
openaire   +2 more sources

Bandit Phase Retrieval

open access: yesCoRR, 2021
We study a bandit version of phase retrieval where the learner chooses actions $(A_t)_{t=1}^n$ in the $d$-dimensional unit ball and the expected reward is $\langle A_t, θ_\star\rangle^2$ where $θ_\star \in \mathbb R^d$ is an unknown parameter vector. We prove that the minimax cumulative regret in this problem is $\smash{\tilde Θ(d \sqrt{n})}$, which ...
Tor Lattimore, Botao Hao
openaire   +3 more sources

Phase Retrieval with Sparse Phase Constraint [PDF]

open access: yesSIAM Journal on Mathematics of Data Science, 2020
For the first time, this paper investigates the phase retrieval problem with the assumption that the phase (of the complex signal) is sparse in contrast to the sparsity assumption on the signal itself as considered in the literature of sparse signal processing.
Nguyen Hieu Thao   +3 more
openaire   +3 more sources

Quantization-aware phase retrieval [PDF]

open access: yesInternational Journal of Wavelets, Multiresolution and Information Processing, 2020
We address the problem of phase retrieval (PR) from quantized measurements. The goal is to reconstruct a signal from quadratic measurements encoded with a finite precision, which is indeed the case in practical applications. We develop an iterative projected-gradient-type algorithm that recovers the signal subject to ensuring consistency with the ...
Subhadip Mukherjee   +1 more
openaire   +2 more sources

Low rank phase retrieval [PDF]

open access: yes2017 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2017
To appear in IEEE Trans.
Seyedehsara Nayer   +2 more
openaire   +2 more sources

AutoPhaseNN: unsupervised physics-aware deep learning of 3D nanoscale Bragg coherent diffraction imaging

open access: yesnpj Computational Materials, 2022
The problem of phase retrieval underlies various imaging methods from astronomy to nanoscale imaging. Traditional phase retrieval methods are iterative and are therefore computationally expensive.
Yudong Yao   +5 more
doaj   +1 more source

Influence of Residual Amplitude and Phase Error for GF-3 Quad-Polarization SAR on Wind Vector Retrieval

open access: yesRemote Sensing, 2022
High-resolution wind vector is important to investigate local winds’ variability over the global ocean. Quad-polarization Synthetic Aperture Radar (SAR) can provide wind vector independently without any external wind direction inputs.
Xiaochen Wang   +5 more
doaj   +1 more source

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