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We consider the problem of calibrating a compressed sensing measurement system under the assumption that the decalibration consists in unknown gains on each measure. We focus on blind calibration, using measures performed on a few unknown (but sparse) signals. A naive formulation of this blind calibration problem, using &#x2113;<sub>1</sub> minimization, is(More)
Regularization of the inverse problem is a complex issue when using near-field acoustic holography (NAH) techniques to identify the vibrating sources. This paper shows that, for convex homogeneous plates with arbitrary boundary conditions, alternative regularization schemes can be developed based on the sparsity of the normal velocity of the plate in a(More)
Measuring the Room Impulse Responses within a finite 3D spatial domain can require a very large number of measurements with standard uniform sampling. In this paper, we show that, at low frequencies, this sampling can be done with significantly less measurements, using some modal properties of the room. At a given temporal frequency, a plane wave(More)
We measured lung volumes, closing volume (CV), alveolo-arterial oxygen difference (P(A-a)O2) and steady-state diffusing lung capacity per liter ventilation (DLCO/V) in 18 men immersed up to the neck in water. The subjects were divided into 3 groups, according to relative changes in P(A-a)O2 and DLCO/V. In group 1 (n = 6), P(A-a)O2 decreased and DLCO/V(More)
The recent theory of compressive sensing leverages upon the structure of signals to acquire them with much fewer measurements than was previously thought necessary, and certainly well below the traditional Nyquist-Shannon sampling rate. However, most implementations developed to take advantage of this framework revolve around controlling the measurements(More)
We have studied the maximal expiratory flow volume curves with air and with an 80% helium-oxygen mixture, using 12 normal and 33 asthmatic children chosen according to clinical, functional and immunological criteria. In the normal children, the average delta Vmax (difference between the maximal flow in HeO2 and in air at corresponding lung volumes) was 49%(More)
Narrowband source localization gets extremely challenging in strong reverberation. When the room is perfectly known, some dictionary-based methods have recently been proposed, allowing source localization with few measurements. In this paper, we first show that, for these methods, the choice of frequencies is important as they fail to localize sources that(More)
In this paper, we investigate the optimal ways to sample multichannel impulse responses, composed of a small number of exponentially damped sinusoids, under the constraint that the total number of samples is fixed &#x2014; for instance with limited storage / computational power. We compute Cram&#x00E9;r-Rao bounds for multichannel estimation of the(More)
449 In this work, a sparsity promoting strategy is developed in order to jointly achieve two complementary tasks regarding sound sources: localization and identification. Here, the sources are assumed sparse in the spatial domain, and greedy algorithms are used for their joint localization and identification in terms of spherical harmonics components. We(More)
We introduce a generalization of the MUSIC algorithm to treat block-sparse signals in a multi-measurement vector framework. We show, through theoretical analysis and numerical experiments, that the requirements in terms of number of snapshots and number of measurements depend not only on the sparsity and on the size of the blocks, but also on the rank of(More)