Category
Time series
Related publications (749)
On the Maximum Power Density of Implanted Antennas within Simplified Body Phantoms
Anja Skrivervik, Zvonimir Sipus, Mingxiang Gao
With the application requirements of wireless technology in implantable bioelectronics, knowledge of the fundamental limits for implanted antennas becomes critical. In this work, we investigated the variation of maximum power density within simplified body ...
IEEE2022Numerical simulations of gas puff imaging using a multi-component model of the neutral-plasma interaction in the tokamak boundary
A three-dimensional simulation of gas puff imaging (GPI) diagnostics is carried out by using a self-consistent multi-component model of the neutral-plasma interaction. The simulation, based on the drift-reduced Braginskii model for the plasma and a kinetic ...
AIP Publishing2022H I constraints from the cross-correlation of eBOSS galaxies and Green Bank Telescope intensity maps
We present the joint analysis of Neutral Hydrogen (H I) Intensity Mapping observations with three galaxy samples: the Luminous Red Galaxy (LRG) and Emission Line Galaxy (ELG) samples from the eBOSS survey, and the WiggleZ Dark Energy Survey sample. The H I ...
OXFORD UNIV PRESS2022Sparsely Observed Functional Time Series: Theory and Applications
Functional time series is a temporally ordered sequence of not necessarily independent random curves. While the statistical analysis of such data has been traditionally carried out under the assumption of completely observed functional data, it may well ha ...
EPFL2021SiML: Sieved Maximum Likelihood for Array Signal Processing
Paul Hurley, Matthieu Martin Jean-André Simeoni
Stochastic Maximum Likelihood (SML) is a popular direction of arrival (DOA) estimation technique in array signal processing. It is a parametric method that jointly estimates signal and instrument noise by maximum likelihood, achieving excellent statistical ...
2021Learning Bollobas-Riordan Graphs Under Partial Observability
This work examines the problem of learning the topology of a network (graph learning) from the signals produced at a subset of the network nodes (partial observability). This challenging problem was recently tackled assuming that the topology is drawn acco ...
IEEE2021Towards 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 ...
2021Activity-based modeling and simulation of epidemics
Michel Bierlaire, Cloe Cortes Balcells, Rico Krüger
The SARS-CoV-2 outburst in March 2020 has led to the lockdown of several countries across the world. Mobility restrictions have been constantly put into action and reversed to find the trade-off between minimizing the number of infections and death and mit ...
2021Efficient Depth-based Deep Learning Methods for Multi-Party Pose Estimation
Human detection and pose estimation are essential components for any artificial system responsive to the presence of humans and that react according to human-centered tasks. Robotic systems are typical examples, for which the body pose represents fine grai ...
EPFL2021SPHARMA approximations for stationary functional time series on the sphere
In this paper, we focus on isotropic and stationary sphere-cross-time random fields. We first introduce the class of spherical functional autoregressive-moving average processes (SPHARMA), which extend in a natural way the spherical functional autoregressi ...
2021