Multi-Frequency Tracking via Group-Sparse Optimal Transport

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Distributed optimization is the standard way of speeding up machine learning training, and most of the research in the area focuses on distributed first-order, gradient-based methods. Yet, there are settings where some computationally-bounded nodes may not ...

Humans and animals both use acoustic signals for vocal communication. The advent of self-supervised learning (SSL) has enabled neural networks to learn robust and general feature representations through the intrinsic acoustic structure of input signals, wi ...

Situational awareness strategies are essential for the reliable and secure operation of the electric power grid which represents critical infrastructure in modern society. With the rise of converter-interfaced renewable generation and the consequent shift ...

Modern power distribution systems are experiencing a large-scale integration of Converter-Interfaced Distributed Energy Resources (CIDERs). Their presence complicates the analysis and mitigation of harmonics, whose creation and propagation may be amplified ...

In the past few years, Machine Learning (ML) techniques have ushered in a paradigm shift, allowing the harnessing of ever more abundant sources of data to automate complex tasks. The technical workhorse behind these important breakthroughs arguably lies in ...

This paper presents a solution to overcome the inherently limited bandwidth of substrate-integrated waveguide (SIW) slot antennas. It is analytically shown that by decreasing the permittivity of a dielectric loaded slot antenna, the resulting bandwidth inc ...

We present a novel technique of neutron noise detection and experimental data interpretation developed during the EU H2020 project CORTEX aiming to improve the capabilities for identification and localization of neutron noise sources. The experimental data ...

RF MEMS piezoelectric acoustic resonators are the essential building blocks for RF filters used in RF front-end modules for wireless mobile communication due to their compact size in the MHz-GHz frequency range, high Quality factors and large relative band ...

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 ...

Space-time (ST) wave packets, in which spatial and temporal characteristics are coupled, have gained attention due to their unique propagation characteristics, such as propagation invariance and tunable group velocity in addition to their potential ability ...

An innovative and very detailed end-to-end system modelling tool has been developed and applied to test on simulated data the actual measurement capabilities of any generic high frequency (HF) magnetic diagnostic systems. The main goal of this rather compl ...

Polynomial neural networks (PNNs) have been recently shown to be particularly effective at image generation and face recognition, where high-frequency information is critical. Previous studies have revealed that neural networks demonstrate a spectral bias ...

The application of unsupervised domain adaptation (UDA)-based fault diagnosis methods has shown significant efficacy in industrial settings, facilitating the transfer of operational experience and fault signatures between different operating conditions, di ...

The millimeter wave (mmWave) frequency band is becoming very interesting over the past years because it provides the opportunity to operate using large bandwidths which are not available at lower frequencies. This enables new communication standards suppor ...

Partial discharge (PD) occurrence in power transformers can lead to irreparable damage to the power network. In this paper, the inverse filter (IF) method to localize PDs in power transformers is proposed. To the best of the authors’ knowledge, this is the ...

Rectified-linear-unit (ReLU) neural networks, which play a prominent role in deep learning, generate continuous and piecewise-linear (CPWL) functions. While they provide a powerful parametric representation, the mapping between the parameter and function s ...

In the analysis of power grid waveforms, the presence of amplitude or phase steps can disrupt the estimation of frequency and rate-of-change-of-frequency (ROCOF). Standard methods based on phasor-models fail in the extraction of signal parameters during th ...

This work presents the study of suspended Y-cut Lithium Niobate shear bulk acoustic resonators for wide band filter applications in the frequency range of 3.5-4.5GHz. The resonators consist of a Lithium Niobate film with Aluminum top interdigitated electro ...

The evaluation of the signal frequency and Rate of Change of Frequency (RoCoF) from voltage or current waveforms is used for critical grid control, monitoring and protection applications. However, when step changes in the amplitude or phase of the signal o ...

Raw data associated to the manuscript ‘’Spin wave dispersion of ultra-low damping hematite (α-Fe2O3) at GHz frequencies‘’, Physical Review Materials 7, 054407(2023); doi: 10.1103/PhysRevMaterials.7.054407 Information about file fo ...

Multi-Frequency Tracking via Group-Sparse Optimal Transport

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Hybrid Decentralized Optimization: Leveraging Both First- and Zeroth-Order Optimizers for Faster Convergence

Transferability of Learnt Speech Representations for Decoding Non-Human Vocal Communication

Functional-Basis Analysis of Non-Stationary Signals in Modern Power Grids: Theory and Implementation in Embedded Systems

Unified Harmonic Power-Flow and Stability Analysis of Power Grids with Converter-Interfaced Distributed Energy Resources

Topics in statistical physics of high-dimensional machine learning

Enabling Wide Bandwidth in Substrate-Integrated Waveguide Slot Antennas by Using Low-Index Metamaterials

Characterization of High Harmonic Frequencies in Reactor Noise Experiments Within the CORTEX Project

Development of Thin Film Lithium Niobate Shear Bulk Acoustic Wave Resonators

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

Generation of OAM-carrying space-time wave packets with time-dependent beam radii using a coherent combination of multiple LG modes on multiple frequencies

Development of algorithms for the end-end system simulation and performance analysis for a high-frequency magnetic diagnostic system: Application to ITER, JET and TCV

The spectral bias of polynomial neural networks

Learnable Wavelet Transform and Domain Adversarial Learning for Enhanced Bearing Fault Diagnosis

Ultra-Low Power Short-Range 60-GHz FMCW Radar Front-End

An Inverse-Filter-Based Method to Locate Partial Discharge Sources in Power Transformers

Stable parameterization of continuous and piecewise-linear functions

Step Change Detection for Improved ROCOF Evaluation of Power System Waveforms

Toward Band n78 Shear Bulk Acoustic Resonators Using Crystalline Y-Cut Lithium Niobate Films With Spurious Suppression

Step detection in power system waveforms for improved RoCoF and frequency estimation

Spin wave dispersion of ultra-low damping hematite (α-Fe2O3) at GHz frequencies