Spread spectrum for imaging techniques in radio interferometry

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We explore applications of quantum computing for radio interferometry and astronomy using recent developments in quantum image processing. We evaluate the suitability of different quantum image representations using a toy quantum computing image reconstruc ...

In inverse problems, the task is to reconstruct an unknown signal from its possibly noise-corrupted measurements. Penalized-likelihood-based estimation and Bayesian estimation are two powerful statistical paradigms for the resolution of such problems. They ...

Experimental measurements of the turbulence amplitude utilizing a short pulse reflectometry method are presented. Two discharges with shaped plasma possessing opposite signs of triangularity are considered and a higher turbulence amplitude is found in the ...

This toolkit has everything you need to perform imaging with a lensless camera. We make use of a low-cost implementation of DiffuserCam, namely replacing the lens with a piece of tape and using the Raspberry Pi HQ camera sensor. Similar principles and meth ...

The usual explanation of the efficacy of wavelet-based methods hinges on the sparsity of many real-world objects in the wavelet domain. Yet, standard wavelet-shrinkage techniques for sparse reconstruction are not competitive in practice, one reason being t ...

In this paper, we investigate the impact of stochasticity and large stepsizes on the implicit regularisation of gradient descent (GD) and stochastic gradient descent (SGD) over diagonal linear networks. We prove the convergence of GD and SGD with macroscop ...

The goal of this thesis is to study continuous-domain inverse problems for the reconstruction of sparse signals and to develop efficient algorithms to solve such problems computationally. The task is to recover a signal of interest as a continuous function ...

Implicit neural representations (INRs) have recently emerged as a promising alternative to classical discretized representations of signals. Nevertheless, despite their practical success, we still do not understand how INRs represent signals. We propose a ...

Starting from a strong Lattice-Free Maximum Mutual Information (LF-MMI) baseline system, we explore different autoencoder configurations to enhance Mel-Frequency Cepstral Coefficients (MFCC) features. Autoencoders are expected to generate new MFCC features ...

The purpose of this Thesis is to develop, test, and characterize different models attempting to tackle the problem of measurement of galaxy shapes applied in interferometric observations. Shape measurement is a tool for estimating the underlying shear due ...

We characterize the solution of a broad class of convex optimization problems that address the reconstruction of a function from a finite number of linear measurements. The underlying hypothesis is that the solution is decomposable as a finite sum of compo ...

Fast and accurate transmission line outage detection can help the central control unit to respond rapidly to better maintain the security and reliability of power systems. It is especially critical in the situation of multiple line outages which is more li ...

Aims. We introduce a novel approach to reconstructing dark matter mass maps from weak gravitational lensing measurements. The cornerstone of the proposed method lies in a new modelling of the matter density field in the Universe as a mixture of two compone ...

Functional time series is a temporally ordered sequence of not necessarily independent random curves. While the statistical analysis of such data has been traditionally carried out under the assumption of completely observed functional data, it may well ha ...

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SAR and optical imagery provide highly complementary information about observed scenes. A combined use of these two modalities is thus desirable in many data fusion scenarios. However, any data fusion task requires measurements to be accurately aligned. Wh ...

We present an overview and description of the e-MERGE Survey (e-MERLIN Galaxy Evolution Survey) Data Release 1 (DR1), a large program of high-resolution 1.5-GHz radio observations of the GOODS-N field comprising similar to 140 h of observations with enhanc ...

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We study the Darcy boundary value problem with lognormal permeability field. We adopt a perturbation approach, expanding the solution in Taylor series around the nominal value of the coefficient, and approximating the expected value of the stochastic solut ...

Spread spectrum for imaging techniques in radio interferometry

Chat with Graph Search

Quantum radio astronomy: Data encodings and quantum image processing

Statistical Inference for Inverse Problems: From Sparsity-Based Methods to Neural Networks

Validation of short-pulse reflectometry turbulence measurements with a synthetic diagnostic

LenslessPiCam: A Hardware and Software Platform for Lensless Computational Imaging with a Raspberry Pi

The Sparsity of Cycle Spinning for Wavelet-Based Solutions of Linear Inverse Problems

(S)GD over Diagonal Linear Networks: Implicit Regularisation, Large Stepsizes and Edge of Stability

Variational Methods For Continuous-Domain Inverse Problems: the Quest for the Sparsest Solution

A Structured Dictionary Perspective on Implicit Neural Representations

From Undercomplete to Sparse Overcomplete Autoencoders to Improve LF-MMI Speech Recognition

Development and evaluation of galaxy shape measurement algorithms for radio interferometric data

Convex optimization in sums of Banach spaces

Multiple Line Outage Detection in Power Systems by Sparse Recovery Using Transient Data

Weak-lensing mass reconstruction using sparsity and a Gaussian random field

Sparsely Observed Functional Time Series: Theory and Applications

Dictionary Learning for Two-Dimensional Kendall Shapes

A deep learning framework for matching of SAR and optical imagery

The e-MERGE Survey (e-MERLIN Galaxy Evolution Survey): overview and survey description

Dynamic Model Pruning with Feedback

Fourier Sampling in Signal Processing and Numerical Linear Algebra

Regularity and sparse approximation of the recursive first moment equations for the lognormal Darcy problem