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
AbstractA computationally-efficient method for recovering sparse signals from a series of noisy obse...
To create multiple sound zones, it is often necessary to get a measure of room impulse responses of ...
The recently introduced theory of compressed sensing enables the reconstruction of sparse or compre...
We consider the estimation of multiple room impulse responses from the simultaneous recording of sev...
International audienceWe consider the estimation of multiple room impulse responses from the simulta...
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...
This paper introduces a method to recover unmeasured room impulse responses (RIRs) in acoustical spa...
International audienceThe goal of this paper is to interpolate Room Impulse Responses (RIRs) within ...
International audienceMeasuring the Room Impulse Responses within a finite 3D spatial domain can req...
42 pages, 37 figures, 3 appendixesInternational audienceCompressed sensing is a signal processing me...
International audienceIn a room, the acoustic transfer between a source and a receiver is described ...
∗(Corresponding author, EURASIP member) Existing convex relaxation-based approaches to reconstructio...
The information management has been treated primarily under the Nyquist sampling theory, but it is i...
Compressed sensing deals with efficient recovery of analog signals from linear encodings. This paper...
AbstractA computationally-efficient method for recovering sparse signals from a series of noisy obse...
To create multiple sound zones, it is often necessary to get a measure of room impulse responses of ...
The recently introduced theory of compressed sensing enables the reconstruction of sparse or compre...
We consider the estimation of multiple room impulse responses from the simultaneous recording of sev...
International audienceWe consider the estimation of multiple room impulse responses from the simulta...
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...
This paper introduces a method to recover unmeasured room impulse responses (RIRs) in acoustical spa...
International audienceThe goal of this paper is to interpolate Room Impulse Responses (RIRs) within ...
International audienceMeasuring the Room Impulse Responses within a finite 3D spatial domain can req...
42 pages, 37 figures, 3 appendixesInternational audienceCompressed sensing is a signal processing me...
International audienceIn a room, the acoustic transfer between a source and a receiver is described ...
∗(Corresponding author, EURASIP member) Existing convex relaxation-based approaches to reconstructio...
The information management has been treated primarily under the Nyquist sampling theory, but it is i...
Compressed sensing deals with efficient recovery of analog signals from linear encodings. This paper...
AbstractA computationally-efficient method for recovering sparse signals from a series of noisy obse...
To create multiple sound zones, it is often necessary to get a measure of room impulse responses of ...
The recently introduced theory of compressed sensing enables the reconstruction of sparse or compre...