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Concept

Noise barrier

Related publications (25)

An Iterative Adaptive Dynamic Programming Approach for Macroscopic Fundamental Diagram-Based Perimeter Control and Route Guidance

Nikolaos Geroliminis

Macroscopic fundamental diagrams (MFDs) have been widely adopted to model the traffic flow of large-scale urban networks. Coupling perimeter control and regional route guidance (PCRG) is a promising strategy to decrease congestion heterogeneity and reduce ...

Informs2024

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

Haitham Al Hassanieh, Junfeng Guan

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 ...

Assoc Computing Machinery2023

Robust Collaborative Learning with Linear Gradient Overhead

Rachid Guerraoui, Nirupam Gupta, Rafaël Benjamin Pinot, Le Nguyen Hoang, Sadegh Farhadkhani, John Stephan

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 ...

PLMR2023

Multi-agent Learning with Privacy Guarantees

Elsa Rizk

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 ...

EPFL2023

Active Wire Fences for Multitenant FPGAs

Mirjana Stojilovic, Ognjen Glamocanin

When spatially shared among multiple tenants, field-programmable gate arrays (FPGAs) are vulnerable to remote power side-channel analysis attacks. Using carefully crafted on-chip voltage sensors, adversaries can extract secrets (e.g., encryption keys or th ...

2023

Plasma-based Electroacoustic Actuator for Broadband Sound Absorption

Stanislav Sergeev

Environmental noise, mostly related to human activities, has an immense impact on public health. The development of noise reduction technologies is paramount in addressing this problem. Because of practical and economic reasons, a compact, broadband, light ...

EPFL2022

A modular functional framework for the design and evaluation of multi-robot navigation

Alcherio Martinoli, Cyrill Silvan Baumann

In this work, we address the design of tightly integrated control, estimation, and allocation algorithms allowing a group of robots to move collectively. For doing so, we leverage a modular framework that allows us to define precisely the needed functional ...

Elsevier2021

Towards the Validation of Noise Experiments in the CROCUS Reactor Using the TRIPOLI-4 Monte Carlo Code in Analog Mode

Andreas Pautz, Vincent Pierre Lamirand, Oskari Ville Pakari

Intrinsic neutron noise experiments offer a non-invasive manner to measure the prompt decay constant or reactivity of fissile systems. Using the fluctuations in the density of fission chains, one can infer the kinetics parameters via correlation analysis s ...

2021

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

Rolf Gruetter, Ileana Ozana Jelescu, Ting Yin, Yujian Diao

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 ...

2021

Low-Power and Wide-Tuning Range Frequency Generation for FMCW Radars in Advanced CMOS Technologies

Francesco Chicco

Nowadays, the internet of things (IoT) nodes have started to spread in various domains of our society, from the industrial to the domestic environment. The remote sensing is one among their fundamental functions. The implementation of a radio detection and ...

EPFL2021

Implicit Bias of SGD for Diagonal Linear Networks: a Provable Benefit of Stochasticity

Nicolas Henri Bernard Flammarion, Scott William Pesme, Loucas Pillaud-Vivien

Understanding the implicit bias of training algorithms is of crucial importance in order to explain the success of overparametrised neural networks. In this paper, we study the dynamics of stochastic gradient descent over diagonal linear networks through i ...

2021

Low Noise Clock Generation: Modeling, Analysis and Implementation

Duygu Kostak

The aim of this thesis is to implement, analyze and improve the selected low noise clock generation and distribution techniques for ADC implementations. The thesis is divided into two parts. The first part focuses on the sampling phase generation and distr ...

EPFL2021

Removing Structured Noise With Self-Supervised Blind-Spot Networks

Martin Weigert

Removal of noise from fluorescence microscopy images is an important first step in many biological analysis pipelines. Current state-of-the-art supervised methods employ convolutional neural networks that are trained with clean (ground-truth) images. Recen ...

IEEE2020

Development of a plasma electroacoustic actuator for active noise control applications

Ivo Furno, Alan Howling, Hervé Lissek, Pénélope Leyland, Gennady Plyushchev, Stanislav Sergeev

Conventional loudspeakers generate sound through the vibration of a diaphragm, attached to a rigid frame through elastic suspensions. Although such construction is satisfactory for sound diffusion in steady environments, it is likely to fail in harsh condi ...

2020

Good Vibrations and Unknown Excitations

Dalia Salem Hassan Fahmy El Badawy

Inspired by the human ability to localize sounds, even with only one ear, as well as to recognize objects using active echolocation, we investigate the role of sound scattering and prior knowledge in regularizing ill-posed inverse problems in acoustics. In ...

EPFL2020

Improving sound absorption through nonlinear active electroacoustic resonators

Romain Christophe Rémy Fleury, Hervé Lissek, Xinxin Guo

Absorbing airborne noise at frequencies below 300 Hz is a particularly vexing problem due to the absence of natural sound absorbing materials at these frequencies. The prevailing solution for low-frequency sound absorption is the use of passive narrow-band ...

American Physical Society (APS)2020

On the effect of linear feedback and parametric pumping on a resonator's frequency stability

Luis Guillermo Villanueva Torrijo, Zohreh Mohammadi

Resonant sensors based on micro- and nano-electro mechanical systems (M/NEMS) are ubiquitous in many sensing applications due to their outstanding performance capabilities, which are directly proportional to the quality factor (Q) of the devices. We addres ...

2020

Extrapolation for Large-batch Training in Deep Learning

Martin Jaggi, Sebastian Urban Stich, Tao Lin

Deep learning networks are typically trained by Stochastic Gradient Descent (SGD) methods that iteratively improve the model parameters by estimating a gradient on a very small fraction of the training data. A major roadblock faced when increasing the batc ...

2020

Reducing Noise in GAN Training with Variance Reduced Extragradient

François Fleuret, Tatjana Chavdarova

We study the effect of the stochastic gradient noise on the training of generative adversarial networks (GANs) and show that it can prevent the convergence of standard game optimization methods, while the batch version converges. We address this issue with ...

2019

Geometry of adversarial robustness of deep networks: methods and applications

Seyed Mohsen Moosavi Dezfooli

We are witnessing a rise in the popularity of using artificial neural networks in many fields of science and technology. Deep neural networks in particular have shown impressive classification performance on a number of challenging benchmarks, generally in ...

EPFL2019