An Accurate kTC Noise Analysis of CDS Circuits

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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 ...

There is a bias in the inference pipeline of most diffusion models. This bias arises from a signal leak whose distribution deviates from the noise distribution, creating a discrepancy between training and inference processes. We demonstrate that this signa ...

Recently, the diffusion moving-average (D-MA) scheme has been proposed as a way to combat noisy links over adaptive networks. However, the current theoretical results focus on networks with mean-square error costs where the optimal local solution agrees wi ...

Designing SPADs with high sensitivity in a wide wavelength range is crucial since the applications utilizing SPAD-based sensors target different parts of the spectrum. Here, we introduce a novel technique to achieve a wider sensitivity spectrum through the ...

A key challenge across many disciplines is to extract meaningful information from data which is often obscured by noise. These datasets are typically represented as large matrices. Given the current trend of ever-increasing data volumes, with datasets grow ...

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 ...

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 ...

This paper proposes a novel method to improve georeferencing of airborne laser scanning by improved trajectory estimation using Vehicle Dynamic Model. In Vehicle Dynamic Model (VDM), the relationship between the dynamics of the platform and control inputs ...

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 ...

As the world’s population grows in cities, urban dwellers spend a large amount of time inside their home, making housing health ever more important. Critical for residents’ health, the interactions between indoor residential environments and outdoor enviro ...

Reinterpretable cameras are defined by their post-processing capabilities that exceed traditional imaging. We present "SoDaCam" that provides reinterpretable cameras at the granularity of photons, from photon-cubes acquired by single-photon devices. Photon ...

The nitrogen-vacancy (NV) center in diamond is a powerful and versatile quantum sensor for diverse quantities. In particular, relaxometry (or T1), can be used to detect magnetic noise at the nanoscale. For experiments with single NV centers the analysis of ...

This paper introduces Wireless IoT-based Noise Cancellation (WINC) which defines a framework for leveraging a wireless network of IoT microphones to enhance active noise cancellation in noise-canceling headphones. The IoT microphones forward ambient noise ...

An analytical expression to estimate the uncertainty on the frequency shift in ϕ-OTDR systems is established and confirmed by actual data. ...

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 ...

Linear-Quadratic-Gaussian (LQG) control is a fundamental control paradigm that is studied in various fields such as engineering, computer science, economics, and neuroscience. It involves controlling a system with linear dynamics and imperfect observations ...

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 ...

This paper demonstrates how to recover causal graphs from the score of the data distribution in non-linear additive (Gaussian) noise models. Using score matching algorithms as a building block, we show how to design a new generation of scalable causal disc ...

The automatic design of well-performing robotic controllers is still an unsolved problem due to the inherently large parameter space and noisy, often hard-to-define performance metrics, especially when sequential tasks need to be accomplished. Distal contr ...

An Accurate kTC Noise Analysis of CDS Circuits

Chat with Graph Search

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

Exploiting the Signal-Leak Bias in Diffusion Models

Diffusion Moving-Average Adaptation Over Networks

A new double multiplication region method to design high sensitivity and wide spectrum SPADs in standard CMOS technologies

Spectral Estimators for High-Dimensional Matrix Inference

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

Disentangling 1/f noise from confined ion dynamics

Functional data analysis with rough sample paths?

Model-based constraints for trajectory determination of quad-copters: Design, calibration & merits for direct orientation

Universal and adaptive methods for robust stochastic optimization

Housing, street and health: a new systemic research framework

SoDaCam: Software-defined Cameras via Single-Photon Imaging

Optimizing Data Processing for Nanodiamond Based Relaxometry

WINC: A Wireless IoT Network for Multi-Noise Source Cancellation

Analytical prediction of the final error due to noise in a ϕ-OTDR system

Multi-agent Learning with Privacy Guarantees

Distributionally Robust Linear Quadratic Control

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

Score Matching Enables Causal Discovery of Nonlinear Additive Noise Models

A Noise-Resistant Mixed-Discrete Particle Swarm Optimization Algorithm for the Automatic Design of Robotic Controllers