International audienceWe consider the estimation of multiple room impulse responses from the simultaneous recording of several known sources. Existing techniques are restricted to the case where the number of sources is at most equal to the number of sensors. We relax this assumption in the case where the sources are known. To this aim, we propose statistical models of the filters associated with convex log-likelihoods, and we propose a convex optimization algorithm to solve the inverse problem with the resulting penalties. We provide a comparison between penalties via a set of experiments which shows that our method allows to speed up the recording process with a controlled quality tradeoff
AbstractIn this paper, we show that in the multiple measurement vector model we can take advantage o...
42 pages, 37 figures, 3 appendixesInternational audienceCompressed sensing is a signal processing me...
International audienceWe investigate a compressive sensing framework in which the sensors introduce ...
International audienceWe consider the estimation of multiple room impulse responses from the simulta...
We consider the estimation of multiple room impulse responses from the simultaneous recording of sev...
International audienceWe propose to acquire large sets of room impulse responses (RIRs) by simultane...
National audienceWe consider the estimation of acoustic impulse responses from the simultaneous reco...
International audienceMeasuring the Room Impulse Responses within a finite 3D spatial domain can req...
Existing convex relaxation-based approaches to reconstruction in compressed sensing assume that nois...
International audienceGiven a sound field generated by a sparse distribution of impulse image source...
This paper introduces a method to recover unmeasured room impulse responses (RIRs) in acoustical spa...
This work is focused on the processing of multichannel and multisource audio signals. From an audio ...
International audienceThe goal of this paper is to interpolate Room Impulse Responses (RIRs) within ...
AbstractIn this paper, we show that in the multiple measurement vector model we can take advantage o...
42 pages, 37 figures, 3 appendixesInternational audienceCompressed sensing is a signal processing me...
International audienceWe investigate a compressive sensing framework in which the sensors introduce ...
International audienceWe consider the estimation of multiple room impulse responses from the simulta...
We consider the estimation of multiple room impulse responses from the simultaneous recording of sev...
International audienceWe propose to acquire large sets of room impulse responses (RIRs) by simultane...
National audienceWe consider the estimation of acoustic impulse responses from the simultaneous reco...
International audienceMeasuring the Room Impulse Responses within a finite 3D spatial domain can req...
Existing convex relaxation-based approaches to reconstruction in compressed sensing assume that nois...
International audienceGiven a sound field generated by a sparse distribution of impulse image source...
This paper introduces a method to recover unmeasured room impulse responses (RIRs) in acoustical spa...
This work is focused on the processing of multichannel and multisource audio signals. From an audio ...
International audienceThe goal of this paper is to interpolate Room Impulse Responses (RIRs) within ...
AbstractIn this paper, we show that in the multiple measurement vector model we can take advantage o...
42 pages, 37 figures, 3 appendixesInternational audienceCompressed sensing is a signal processing me...
International audienceWe investigate a compressive sensing framework in which the sensors introduce ...