Study of vehicle noise for different operating conditions

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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 ...

Path-following control is a critical technology for autonomous vehicles. However, time-varying parameters, parametric uncertainties, external disturbances, and complicated environments significantly challenge autonomous driving. We propose an iterative rob ...

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 ...

Noise measurements in light water reactor systems aid in generating validation data for integral point kinetic parameter predictions and generating monitoring parameters for reactor safety and safeguards. The CROCUS zero-power reactor has been used to supp ...

We study the hitting probabilities of the solution to a system of d stochastic heat equations with additive noise subject to Dirichlet boundary conditions. We show that for any bounded Borel set with positive (d-6)\documentclass[12pt]{minimal} \usepackage{ ...

In this paper, we study sampling from a posterior derived from a neural network. We propose a new probabilistic model consisting of adding noise at every pre- and post-activation in the network, arguing that the resulting posterior can be sampled using an ...

In the context of smart cities, ensuring road safety is crucial due to increasing urbanization and the interconnected nature of contemporary urban environments. Leveraging innovative technologies is essential to mitigate risks and create safer communities. ...

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 ...

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 ...

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 ...

Data for: "A Neural-Network-Based Convex Regularizer for Inverse Problems". The corresponding scripts can be accessed on GitHub (https://github.com/axgoujon/convex_ridge_regularizers). The data is organized as follows: - ct_data_sets.tar.gz: contains prepr ...

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 ...

Air traffic noise emissions are responsible for a significant part of the overall environmental noise, especially in the vicinity of airports. Exposure to environmental noise is known to negatively impact health and to be associated with cardiovascular dis ...

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 ...

Reciprocity guarantees that in most media, sound transmission is symmetric between two points of space when the location of the source and receiver are interchanged. This fundamental law can be broken in non-linear media, often at the cost of detrimental i ...

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 ...

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 ...

Control systems operating in real-world environments often face disturbances arising from measurement noise and model mismatch. These factors can significantly impact the perfor- mance and safety of the system. In this thesis, we aim to leverage data to de ...

Collaborative learning algorithms, such as distributed SGD (or D-SGD), are prone to faulty machines that may deviate from their prescribed algorithm because of software or hardware bugs, poisoned data or malicious behaviors. While many solutions have been ...

Study of vehicle noise for different operating conditions

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

Less Conservatism, Stronger Robustness: Iterative Robust Gain-Scheduled Path Following Control of Autonomous Bus With Unstructured and Changing Dynamics

Exploiting the Signal-Leak Bias in Diffusion Models

Neutron-Gamma Noise Measurements in a Zero-Power Reactor Using Organic Scintillators

Hitting with Probability One for Stochastic Heat Equations with Additive Noise

Gibbs sampling the posterior of neural networks

Artificial intelligence of things for smart cities: advanced solutions for enhancing transportation safety

Spectral Estimators for High-Dimensional Matrix Inference

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

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

Data for: "A Neural-Network-Based Convex Regularizer for Inverse Problems"

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

Disentangling 1/f noise from confined ion dynamics

Robust tunable acoustic impedance control on electroacoustic resonators for aircraft noise reduction

Multi-agent Learning with Privacy Guarantees

Observation of non-reciprocal harmonic conversion in real sounds

Universal and adaptive methods for robust stochastic optimization

Functional data analysis with rough sample paths?

Data-Driven Control and Optimization under Noisy and Uncertain Conditions

Robust Collaborative Learning with Linear Gradient Overhead