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We consider multiple description coding for the Gaussian source with K descriptions under the symmetric mean squared error distortion constraints. One of the main contributions is a novel lower bound on the sum rate, derived by generalizing Ozarow’s well-k ...
\begin{abstract} In this paper, we address an adaptive beamforming application in realistic acoustic conditions. After the position of a speaker is estimated by a speaker tracking system, we construct a subband-domain beamformer in \emph{generalized sidelo ...
We consider the problem of transmitting a Gaussian source on a slowly fading Gaussian channel, subject to the mean-squared error distortion measure. The channel state information is known only at the receiver but not at the transmitter. The source is assum ...
We consider the problem of optimizing the parameters of an arbitrary denoising algorithm by minimizing Stein's Unbiased Risk Estimate (SURE) which provides a means of assessing the true mean-squared-error (MSE) purely from the measured data assuming that i ...
We consider the problem of optimizing the parameters of an arbitrary denoising algorithm by minimizing Stein's Unbiased Risk Estimate (SURE) which provides a means of assessing the true mean-squared-error (MSE) purely from the measured data assuming that i ...
Ieee Service Center, 445 Hoes Lane, Po Box 1331, Piscataway, Nj 08855-1331 Usa2008
A single memoryless Gaussian source is observed by many terminals, subject to independent Gaussian observation noises. The terminals are linked to a fusion center via a standard Gaussian multiple-access channel. The fusion center needs to recover the under ...
In this correspondence, we consider the multiuser successive refinement (MSR) problem, where the users are connected to a central server via links with different noiseless capacities, and each user wishes to reconstruct in a successive-refinement fashion. ...
We introduce here a new universality conjecture for levels of random Hamiltonians, in the same spirit, as the local REM conjecture made by S. Mertens and H. Bauke. We establish our conjecture for a wide class of Gaussian and non-Gaussian Hamiltonians, whic ...
Birkhauser Boston, C/O Springer-Verlag, Service Center, 44 Hartz Way, Secaucus, Nj 07096-2491 Usa2008
Bayesian nonparametric models are widely and successfully used for statistical prediction. While posterior consistency properties are well studied in quite general settings, results have been proved using abstract concepts such as metric entropy, and they ...
Institute of Electrical and Electronics Engineers2008
The decomposition of a signal on the sphere with the steerable wavelet constructed from the second Gaussian derivative gives access to the orientation, signed-intensity and elongation of the signal’s local features. In the present work, the non-Gaussianity ...
