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Publications associées (30)

Compound Admittance Matrix Estimation of Three-phase Untransposed Power Distribution Grids using Synchrophasor Measurements

Mario Paolone, Jean-Yves Le Boudec, Fabrizio Sossan, Rahul Kumar Gupta

The paper considers the problem of estimating the parameters of the compound admittance matrix of three-phase untransposed low-and medium-voltage electrical distribution networks using synchrophasor measurements from phasor measurement units (PMUs). The wo ...

2021

Using footstep-induced vibrations for occupant detection and recognition in buildings

Ian Smith, Yves Sylvain Gilles Reuland, Sai Ganesh Sarvotham Pai, Slah Drira

Occupant detection and recognition support functional goals such as security, healthcare, and energy management in buildings. Typical sensing approaches, such as smartphones and cameras, undermine the privacy of building occupants and inherently affect the ...

2021

Impact of optical noises on unipolar-coded Brillouin optical time-domain analyzers

Luc Thévenaz, Marcelo Alfonso Soto Hernandez, Zhisheng Yang, Sheng Wang

Noise models for both single-pulse and coded Brillouin optical time-domain analyzers (BOTDA) are established to quantify the actual signal-to-noise ratio (SNR) enhancement provided by pulse coding at any fiber position and in any operating condition. Simul ...

2021

Motor state transitions and Breathing in Brain Machine Interfaces

Bastien Orset

Brain-Machine interfaces aim to create a direct neural link between user's brain and machines. This goal has pushed scientists to investigate a large spectrum of applications in the realm of assistive and rehabilitation technologies. However, despite great ...

EPFL2021

Wasserstein Adversarial Regularization for learning with label noise

Devis Tuia

Noisy labels often occur in vision datasets, especially when they are obtained from crowdsourcing or Web scraping. We propose a new regularization method, which enables learning robust classifiers in presence of noisy data. To achieve this goal, we propose ...

2021

Mean-Field Games And Swarms Dynamics In Gaussian And Non-Gaussian Environments

Max-Olivier Hongler

The collective behaviour of stochastic multi-agents swarms driven by Gaussian and non-Gaussian environments is analytically discussed in a mean-field approach. We first exogenously implement long range mutual interactions rules with strengths that are weig ...

AMER INST MATHEMATICAL SCIENCES-AIMS2020

Partial Discharge Localization Using Time Reversal: Application to Power Transformers

Farhad Rachidi-Haeri, Marcos Rubinstein, Mohammad Azadifar, Amirhossein Mostajabi, Hamidreza Karami

In this work, we present a novel technique to locate partial discharge (PD) sources based on the concept of time reversal. The localization of the PD sources is of interest for numerous applications, including the monitoring of power transformers, Gas Insu ...

2020

Long-term evolution of Landau damping in the presence of transverse noise, feedback, and detuning

Xavier Buffat, Sondre Vik Furuseth

The effect of Landau damping is often calculated assuming a Gaussian beam distribution in all transverse degrees of freedom, which agrees reasonably well with beam measurements. However, the stability of the beam is strongly dependent on the details of the ...

2020

Occupancy detection and tracking in buildings using floor-vibration signals

Slah Drira

In sensed buildings, information related to occupant movement helps optimize important functionalities such as security enhancement, energy management, and caregiving. Typical sensing approaches for occupant tracking rely on mobile devices and cameras. The ...

EPFL2020

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