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We consider the incompressible Euler equations in two or three dimensions and we show that the addition of a suitable multiplicative It? noise with superlinear growth prevents a smooth solution from b...
In this talk, we present the pointwise convergence of one-point large deviations rate functions (LDRFs) of the spatial finite difference method and further the fully discrete method based on the tempo...
Hands-free operation of a mobile phone in car raises major challenges for acoustic enhancement algorithms and speech recognition engines. This is due to a degradation of the speech signal caused by re...
Few source separation and independent component analysis approaches attempt to deal with noisy data. Weconsider an additive noise mixing model with an arbitrary number of sensors and possibly more sou...
To be applicable in realistic scenarios, blind source separation approaches should deal evenly with non-square cases and the presence of noise. We consider an additive noisemixing model with an arbitr...
This paper compares wavelet and short time Fourier transform based techniques for single channel speechsignal noise reduction. Despite success of wavelet denoising of images, it has not yet been widel...
Accurate noise power spectrum estimation in a noisy speech signal is a key challenge problem in speech enhancement.One state-of-the-art approach is the minima controlledrecursive averaging (MCRA). Thi...
We consider the statistical experiment given by a sample y(1), . . . , y(n) of a stationary Gaussian process with an unknown smooth spectral density f. Asymptotic equivalence, in the sense of Le Cam’s...
We consider the statistical experiment given by a sample y(1), . . . , y(n) of a stationary Gaussian process with an unknown smooth spectral density f . Asymptotic equivalence, in the sense of Le Cam’...
We study extremal problems related to nonparametric maximum likelihood estimation (MLE) of a signal in white noise.The aim is to reduce these to standard problems of optimal control which can be solve...
Signal recovery in Gaussian white noise with variance tending to zero has served for some time as a representative model for nonparametric curve estimation, having all the essential traits in a pure f...
Signal recovery in Gaussian white noise with variance tending to zero has served for some time as a representative model for nonparametric curve estimation, having all the essential traits in a pure f...
On the heels of compressed sensing, a remarkable new field has very recently emerged. This field addresses a broad range of problems of significant practical interest, namely, the recovery of a data m...
The Navier-Stoke s e quations are the fundame ntal m o de l of the fluids . De spite t he ir gre at physic al im p ortance , exist ence and uniquenes s res ults for the e quations in the three -dime...
This document derives several expected values related to the parameterized mean model with Gaussian noise and their simplified forms.

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