SURE-LET for Orthonormal Wavelet-Domain Video Denoising

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We prove global in time well-posedness for perturbations of the 2D stochastic Navier-Stokes equations partial derivative( t)u + u center dot del u = Delta u - del p + sigma + xi, u(0, center dot ) = u(0),div (u) = 0, driven by additive space-time white noi ...

Photometric stereo, a computer vision technique for estimating the 3D shape of objects through images captured under varying illumination conditions, has been a topic of research for nearly four decades. In its general formulation, photometric stereo is an ...

Within the context of contemporary machine learning problems, efficiency of optimization process depends on the properties of the model and the nature of the data available, which poses a significant problem as the complexity of either increases ad infinit ...

A multi-agent system consists of a collection of decision-making or learning agents subjected to streaming observations from some real-world phenomenon. The goal of the system is to solve some global learning or optimization problem in a distributed or dec ...

Ion transport through biological and solid-state nanochannels is known to be a highly noisy process. The power spectrum of current fluctuations is empirically known to scale like the inverse of frequency, following the long-standing yet poorly understood H ...

Functional data are typically modeled as sample paths of smooth stochastic processes in order to mitigate the fact that they are often observed discretely and noisily, occasionally irregularly and sparsely. The smoothness assumption is imposed to allow for ...

Remote photoplethysmography (rPPG) using camera-based imaging has shown excellent potential recently in vital signs monitoring due to its contactless nature. However, the optimum filter selection for pre-processing rPPG data in signal conditioning is still ...

Eccentricity has emerged as a potentially useful tool for helping to identify the origin of black hole mergers. However, eccentric templates can be computationally very expensive owing to the large number of harmonics, making statistical analyses to distin ...

Image noise can often be accurately fitted to a Poisson-Gaussian distribution. However, estimating the distribution parameters from a noisy image only is a challenging task. Here, we study the case when paired noisy and noise-free samples are accessible. N ...

Ion-sensitive field-effect transistors (ISFETs) form a high sensitivity and scalable class of sensors, compatible with advanced complementary metal-oxide semiconductor (CMOS) processes. Despite many previous demonstrations about their merits as low-power i ...

This article addresses the problem of simultaneous distributed state estimation, and control of linear systems with linear state feedback, subjected to process, and measurement noise, under the constraints of quantized, and rate-limited network data transm ...

High-energy hadron colliders are designed to generate particle collisions within specialized detectors. A higher number of collisions is achieved with high-quality beams of low transverse emittances, meaning a small transverse cross-section, and high inten ...

Laser phase noise remains a limiting factor in many experimental settings, including metrology, time-keeping, as well as quantum optics. Hitherto this issue was addressed at low frequencies ranging from well below 1 Hz to maximally 100 kHz. However, a wide ...

Stochastic Maximum Likelihood (SML) is a popular direction of arrival (DOA) estimation technique in array signal processing. It is a parametric method that jointly estimates signal and instrument noise by maximum likelihood, achieving excellent statistical ...

This database is meant to evaluate the performance of denoising and delineation algorithms for PPG signals affected by noise. The noise generator allows applying the algorithms under test to an artificially corrupted reference PPG signal and comparing its ...

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 ...

Resting state functional MRI (rs-fMRI) is a widespread and powerful tool for investigating functional connectivity (FC) and brain disorders. However, FC analysis can be seriously affected by random and structured noise from non-neural sources, such as phys ...

Nowadays, efficient and remote health monitoring is becoming increasingly important, given both the ageing of population and the combined action of an increase in obesity level and cardiovascular diseases. The healthcare industry is becoming more reliant o ...

Objective. Among the different approaches for denoising neural signals, wavelet-based methods are widely used due to their ability to reduce in-band noise. All wavelet denoising algorithms have a common structure, but their effectiveness strongly depends o ...

The low-light performance of a CMOS image sensor (CIS) is one of the most important performance metrics in a camera, whether it is used in products for consumer electronics or in an image-acquisition system for machine vision or the Internet-of-Things (IoT ...

SURE-LET for Orthonormal Wavelet-Domain Video Denoising

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Global existence for perturbations of the 2D stochastic Navier-Stokes equations with space-time white noise

Aggregating Spatial and Photometric Context for Photometric Stereo

Universal and adaptive methods for robust stochastic optimization

Multi-agent Learning with Privacy Guarantees

Disentangling 1/f noise from confined ion dynamics

Functional data analysis with rough sample paths?

Optimal digital filter selection for remote photoplethysmography (rPPG) signal conditioning

An Efficient Signal-to-noise Approximation for Eccentric Inspiraling Binaries

PoGaIN: Poisson-Gaussian Image Noise Modeling From Paired Samples

Sensitivity, Noise and Resolution in a B -Modified Foundry-Made ISFET with Miniaturized Reference Electrode for Wearable Point-of-Care Applications

A Distributed Luenberger Observer for Linear State Feedback Systems With Quantized and Rate-Limited Communications

Transverse Noise, Decoherence, and Landau Damping in High-Energy Hadron Colliders

High-frequency broadband laser phase noise cancellation using a delay line

SiML: Sieved Maximum Likelihood for Array Signal Processing

Synthetic realistic noise-corrupted PPG database and noise generator for the evaluation of PPG denoising and delineation algorithms

Sparsely Observed Functional Time Series: Theory and Applications

PIRACY: An Optimized Pipeline for Functional Connectivity Analysis in the Rat Brain

An Ultra Low-Noise Micropower PPG Sensor

Systematic analysis of wavelet denoising methods for neural signal processing

Modeling for Ultra Low Noise CMOS Image Sensors