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Distributed sensing of noisy signals by thresholding of redundant expansions

Publications associées (74)

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Phase AutoCorrelation (PAC) derived Robust Speech Features

Hervé Bourlard, Hemant Misra, Shajith Ikbal

In this paper, we introduce a new class of noise robust acoustic features derived from a new measure of autocorrelation, and explicitly exploiting the phase variation of the speech signal frame over time. This family of features, referred to as ``Phase Aut ...

2003

Sampling signals with finite rate of innovation: the noisy case

Martin Vetterli, Andrea Ridolfi, Irena Maravic

Recently a sampling theorem for a certain class of signals with finite rate of innovation (which includes for example stream of Diracs) has been developed. In essence, such non band-limited signals can be sampled at or above the rate of innovation. In the ...

2002

Microphone Array Post-filter for Diffuse Noise Field

Hervé Bourlard

This paper proposes a novel technique for estimating the signal power spectral density to be used in the transfer function of a microphone array post-filter. The technique is a modification of the existing Zelinski post-filter, which uses the auto- and cro ...

2002

Phase AutoCorrelation (PAC) derived Robust Speech Features

Hervé Bourlard, Hemant Misra, Shajith Ikbal

IDIAP2002

Microphone Array Post-filter based on Noise Field Coherence

Hervé Bourlard

This article introduces a novel technique for estimating the signal power spectral density to be used in the transfer function of a microphone array post-filter. The technique is a generalisation of the existing Zelinski post-filter, which uses the auto- a ...

IDIAP2001

Microphone Array Post-filter for Diffuse Noise Field

Hervé Bourlard

IDIAP2001

Wavelet thresholding for multiple noisy images

Martin Vetterli

This correspondence addresses the recovery of an image from its multiple noisy copies. The standard method is to compute the weighted average of these copies. Since the wavelet thresholding technique has been shown to effectively denoise a single noisy cop ...

2000

Measuring the complexity of time series: an application to neurophysiological signals

Olaf Blanke

Measures of signal complexity can be used to distinguish neurophysiological activation from noise in those neuroimaging techniques where we record variations of brain activity with time, e.g., fMRI, EEG, ERP. In this paper we explore a recently developed a ...

Wiley-Blackwell2000

Multichannel Restoration with Limited A Priori Information

Michaël Unser

We introduce a method for multichannel restoration of images in which there is severely limited knowledge about the undegraded signal, and possibly the noise. We assume that we know the channel degradations and that there will be a significant noise reduct ...

IEEE1999

Calcul stochastique appliqué aux problèmes de détection des signaux aléatoires

Signal detection is one of the basic problems in statistical communication theory, and has many applications to contemporary technology, whether in engineering, medical science, or the environment. The most difficult problems are those involving random sig ...

EPFL1999