Sampling Continuous-time Sparse Signals: A Frequency-domain Perspective

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The usual explanation of the efficacy of wavelet-based methods hinges on the sparsity of many real-world objects in the wavelet domain. Yet, standard wavelet-shrinkage techniques for sparse reconstruction are not competitive in practice, one reason being t ...

We generalize and provide a linear algebra-based perspective on a finite element (FE) ho-mogenization scheme, pioneered by Schneider et al. (2017)[1] and Leuschner and Fritzen (2018)[2]. The efficiency of the scheme is based on a preconditioned, well-scale ...

Chatter is a harmful self-excited vibration that commonly occurs during milling processes. Data -driven chatter detection and prediction is critical to achieve high surface quality and process efficiency. Most existing chatter detection approaches are base ...

We introduce the elliptical Ornstein-Uhlenbeck (OU) process, which is a generalisation of the well-known univariate OU process to bivariate time series. This process maps out elliptical stochastic oscillations over time in the complex plane, which are obse ...

Is it possible to detect if the sample paths of a stochastic process almost surely admit a finite expansion with respect to some/any basis? The determination is to be made on the basis of a finite collection of discretely/noisily observed sample paths. We ...

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A kernel method for estimating a probability density function from an independent and identically distributed sample drawn from such density is presented. Our estimator is a linear combination of kernel functions, the coefficients of which are determined b ...

A correct representation of the lightning current is crucial when the electromagnetic field radiated to a point of interest has to be computed. Based on the engineering models of Transmission Line type, such representation involves the knowledge of the ret ...

The goal of this thesis is to study continuous-domain inverse problems for the reconstruction of sparse signals and to develop efficient algorithms to solve such problems computationally. The task is to recover a signal of interest as a continuous function ...

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 ...

Capturing high-frequency data concerning the condition of complex systems, e.g. by acoustic monitoring, has become increasingly prevalent. Such high-frequency signals typically contain time dependencies ranging over different time scales and different type ...

Sampling Continuous-time Sparse Signals: A Frequency-domain Perspective

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

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

Statistical Inference for Inverse Problems: From Sparsity-Based Methods to Neural Networks

Shuffled multi-channel sparse signal recovery

Disentangling Thermal from Electronic Contributions in the Spectral Response of Photoexcited Perovskite Materials

Multi-Frequency Tracking via Group-Sparse Optimal Transport

Modeling friction and wear using an adaptive discrete-continuum coupling

Impact of beam-coupling impedance on the Schottky spectrum of bunched beam

The Sparsity of Cycle Spinning for Wavelet-Based Solutions of Linear Inverse Problems

An optimal preconditioned FFT-accelerated finite element solver for homogenization

Exploring the effectiveness of using internal CNC system signals for chatter detection in milling process

The elliptical Ornstein-Uhlenbeck process

Detecting whether a stochastic process is finitely expressed in a basis

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

Smart filter aided domain adversarial neural network for fault diagnosis in noisy industrial scenarios

Density estimation in RKHS with application to Korobov spaces in high dimensions

On the reconstruction of the attenuation function of a return-stroke current from the Fourier Transform of finite-duration measurements

Variational Methods For Continuous-Domain Inverse Problems: the Quest for the Sparsest Solution

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

Learnable Wavelet Packet Transform for Data-Adapted Spectrograms