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Compressed sensing (CS) deals with the reconstruction of sparse signals from a small number of linear measurements. One of the main challenges in CS is to find the support of a sparse signal from a set of noisy observations. In the CS literature, several i ...
Compressed sensing (CS) deals with the reconstruction of sparse signals from a small number of linear measurements. One of the main challenges in CS is to find the support of a sparse signal from a set of noisy observations. In the CS literature, several i ...
This research explores the links between social exclusion, car dependence and public policies for members of non-motorized households who are potentially socially excluded. It is at the crossroads of urban sociology, public policy and transport geography. ...
Motivated by the seismic response of unanchored liquid storage tanks, their uplift mechanism under strong lateral loading is examined. Using three-dimensional finite element models, nonlinear static analysis is conducted to define the moment-rotation relat ...
Many recent works have shown that if a given signal admits a sufficiently sparse representation in a given dictionary, then this representation is recovered by several standard optimization algorithms, in particular the convex ℓ1 minimization approac ...
This article investigates an innovative concept of vehicle propulsion. An electric vehicle with limited battery packs is coupled with an innovative converter – a Solid Oxide Fuel Cell with gas turbines system (SOFC- GT). This energy integrated converter is ...
