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High-resolution deconvolution applied to non destructive testing
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An overview of inverse problem regularization using sparsity
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Anisotropic oracle inequalities in noisy quantization
The effect of errors in variables in quantization is investigated. We prove general exact and non-exact oracle inequalities with fast rates for an empirical... -
Relative extents of preformation and neoformation in tree shoots: Analysis by...
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Adaptive Noisy Clustering
The problem of adaptive noisy clustering is investigated. Given a set of noisy observations $Z_i=X_i+\epsilon_i$, $i=1, \ldots, n$, the goal is to design clusters... -
Can Rock-Eval pyrolysis assess the biogeochemical composition of organic matt...
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Noisy classification with boundary assumptions
We address the problem of classification when data are collected from two samples with measurement errors. This problem turns to be an inverse problem and requires a... -
Algebraic and determinist identification of continuous-time signals and syste...
This thesis is concerned with the problem of signals and systems identification applied to digital communication. While<br />the majority of the existing methods... -
The algorithm of noisy k-means
In this note, we introduce a new algorithm to deal with finite dimensional clustering with errors in variables. The design of this algorithm is based on recent... -
Generalized mutual information approach to multichannel blind deconvolution
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Robust wavelet estimation and blind deconvolution of noisy surface seismics
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Robust wavelet estimation and blind deconvolution of noisy surface seismics
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Bayesian Joint Detection-Estimation of cerebral vasoreactivity from ASL fMRI ...
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Towards interval-based non-additive deconvolution in signal processing
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Towards a Robust Imprecise Linear Deconvolution
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Improvement of the LLS and MAP deconvolution algorithms by automatic determin...
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Adaptive parameter selection for block wavelet-thresholding deconvolution
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Deconvolution and separation of hyperspectral images. Applications to microscopy
Hyperspectral imaging refers to the acquisition of spatial images at enough spectral bands to produce highly resolved pixel spectra. When applied to microscopy, this... -
Does deblurring improve geometrical hyperspectral unmixing?
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New adaptive strategies for nonparametric estimation in linear mixed models
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