activity
20172021
most citedMulti-Marginal Optimal Mass Transport with Partial Information

3 citations · 4 across the 3 of their papers we have counts for

collaborators

9 papers

eess.SP2021

Determining Joint Periodicities in Multi-time Data With Sampling Uncertainties

David Svedberg, Filip Elvander, Andreas Jakobsson

In this work, we introduce a novel approach for determining a joint sparse spectrum from several non-uniformly sampled data sets, where each data set is assumed to have its own, po…

eess.SP2020

Defining Fundamental Frequency for Almost Harmonic Signals

Filip Elvander, Andreas Jakobsson

In this work, we consider the modeling of signals that are almost, but not quite, harmonic, i.e., composed of sinusoids whose frequencies are close to being integer multiples of a…

eess.SP2019

Compressed Sensing for Reconstructing Coherent Multidimensional Spectra

Zhengjun Wang, Shiwen Lei, Khadga Jung Karki +2

We apply two sparse reconstruction techniques, the least absolute shrinkage and selection operator (LASSO) and the sparse exponential mode analysis (SEMA), to two-dimensional (2D)…

eess.SP2019

On Harmonic Approximations of Inharmonic Signals

Filip Elvander, Jie Ding, Andreas Jakobsson

In this work, we present the misspecified Gaussian Cramér-Rao lower bound for the parameters of a harmonic signal, or pitch, when signal measurements are collected from an almost,…

eess.SP2019

Mismatched Estimation of Polynomially Damped Signals

Filip Elvander, Johan Swärd, Andreas Jakobsson

In this work, we consider the problem of estimating the parameters of polynomially damped sinusoidal signals, commonly encountered in, for instance, spectroscopy. Generally, findin…

eess.SP20193 cited

Multi-Marginal Optimal Mass Transport with Partial Information

Filip Elvander, Isabel Haasler, Andreas Jakobsson +1

During recent decades, there has been a substantial development in optimal mass transport theory and methods. In this work, we consider multi-marginal problems wherein only partial…