Thomas Trigano

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Negative co-occurrence is a common phenomenon in many signal processing applications. In some cases the signals involved are sparse, and this information can be exploited to recover them. In this paper, we present a sparse learning approach that explicitly takes into account negative co-occurrence. This is achieved by adding a novel penalty term to the(More)
Assume that we observe a large number of signals, all of them with identical, although unknown, shape, but with a different random shift. The objective is to estimate the individual time shifts and their distribution. Such an objective appears in several biological applications like neuroscience or ECG signal processing, in which the estimation of the(More)
In this paper we try to address the problem of curve alignment with a semiparametric framework, that is without any knowledge of the shape. This study stems from a biological issue, in which we are interested in the estimation of the average heart cycle signal, but wish to estimate it without any knowledge of the pulse shape, which may differ from one(More)
The problem of blind sparse analysis of electrogram (EGM) signals under atrial fibrillation (AF) conditions is considered in this paper. A mathematical model for the observed signals that takes into account the multiple foci typically appearing inside the heart during AF is firstly introduced. Then, a reconstruction model based on a fixed dictionary is(More)
In this paper, a new method is presented to ensure automatic synchronization of intracardiac ECG data, yielding a three-stage algorithm. We first compute a robust estimate of the derivative of the data to remove low-frequency perturbations. Then we provide a grouped-sparse representation of the data, by means of the Group LASSO, to ensure that all the(More)
We consider the counting rate estimation of an unknown radioactive source, which emits photons at times modeled by an homogeneous Poisson process. A spectrometer converts the energy of incoming photons into electrical pulses, whose number provides a rough estimate of the intensity of the Poisson process. When the activity of the source is high, a physical(More)
The aim of nuclear spectroscopy is to provide as many information as possible regarding the activity and the content of an unknown radioactive source. Due to some random perturbations called pileup phenomenon, electrical pulses recorded by the spectrometric apparatus may overlap. Recent developments in compressive sensing and sparse signal reconstruction(More)