Zobrazeno 1 - 9
of 9
pro vyhledávání: '"Idier, J��r��me"'
In this paper the problem of restoration of non-negative sparse signals is addressed in the Bayesian framework. We introduce a new probabilistic hierarchical prior, based on the Generalized Hyperbolic (GH) distribution, which explicitly accounts for
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::9777a4a91f4351304ae4eb757c1fc0ef
http://arxiv.org/abs/2102.06081
http://arxiv.org/abs/2102.06081
In a low-statistics PET imaging context, the positive bias in regions of low activity is a burning issue. To overcome this problem, algorithms without the built-in non-negativity constraint may be used. They allow negative voxels in the image to redu
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::e10a168c83264d6e77c589f454c92a46
Sparse signal restoration is usually formulated as the minimization of a quadratic cost function $\|y-Ax\|_2^2$, where A is a dictionary and x is an unknown sparse vector. It is well-known that imposing an $\ell_0$ constraint leads to an NP-hard mini
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::0d167f1fb015df5fde207380d55a35b6
http://arxiv.org/abs/1406.4802
http://arxiv.org/abs/1406.4802
The resolution of many large-scale inverse problems using MCMC methods requires a step of drawing samples from a high dimensional Gaussian distribution. While direct Gaussian sampling techniques, such as those based on Cholesky factorization, induce
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::ea8e05221e9ded6f894011d8ffedf02b
Tropp's analysis of Orthogonal Matching Pursuit (OMP) using the Exact Recovery Condition (ERC) is extended to a first exact recovery analysis of Orthogonal Least Squares (OLS). We show that when the ERC is met, OLS is guaranteed to exactly recover th
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::782554b8dad36e49601f1a2680d87e4a
Autor:
F��votte, C��dric, Idier, J��r��me
This paper describes algorithms for nonnegative matrix factorization (NMF) with the beta-divergence (beta-NMF). The beta-divergence is a family of cost functions parametrized by a single shape parameter beta that takes the Euclidean distance, the Kul
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https://explore.openaire.eu/search/publication?articleId=doi_________::97a275945e2558abe47be20b6d3ea09e
This research report summarizes the progress of work carried out jointly by the IRCCyN and the ��cole Polytechnique de Montr��al about the resolution of the inverse problem for the seismic imaging of transmission overhead line structure found
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https://explore.openaire.eu/search/publication?articleId=doi_________::7f3cd9e3f255382f9c22b85ad898074b
This paper deals with improvements to the contrast source inversion method which is widely used in microwave tomography. First, the method is reviewed and weaknesses of both the criterion form and the optimization strategy are underlined. Then, two n
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::9fc48cde2dbaea16b168a5de2d171b2a
http://arxiv.org/abs/0901.4723
http://arxiv.org/abs/0901.4723
Autor:
Mohammad-Djafari, A., Idier, J��r��me
In this paper we propose a new Bayesian estimation method to solve linear inverse problems in signal and image restoration and reconstruction problems which has the property to be scale invariant. In general, Bayesian estimators are {\em nonlinear} f
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::6caa823f1f7fe9210a5d9bfb20e80150