Zobrazeno 1 - 10
of 58
pro vyhledávání: '"Maher Moakher"'
Publikováno v:
PLoS ONE, Vol 10, Iss 4, p e0121423 (2014)
We explore the connection between two problems that have arisen independently in the signal processing and related fields: the estimation of the geometric mean of a set of symmetric positive definite (SPD) matrices and their approximate joint diagona
Externí odkaz:
https://doaj.org/article/5ae205f10cc445b4baa01a26e2c993af
Publikováno v:
Mathematical Methods in the Applied Sciences. 46:6324-6358
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::270b3f8758f2d891f9847e42a6c18c3e
https://doi.org/10.1002/mma.8905
https://doi.org/10.1002/mma.8905
Publikováno v:
Mathematics and Computers in Simulation. 188:77-86
In this paper we present an algorithm for solving quasi-pentadiagonal Toeplitz linear systems, that is based on Du et al. method (Du et al., 2014) and the Sherman–Morrison–Woodbury inversion formula. All algorithms have been implemented in Matlab
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::da9f365472fd59b05f8b7022307764ab
https://doi.org/10.1016/j.matcom.2021.03.031
https://doi.org/10.1016/j.matcom.2021.03.031
Publikováno v:
Computational and Applied Mathematics. 41
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::15ea08ee8dc45611b7cb6c856687f142
https://doi.org/10.1007/s40314-022-02020-z
https://doi.org/10.1007/s40314-022-02020-z
Publikováno v:
New Trends in Mathematical Science. 4:421-440
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::f4b8b1c9134adcaee6ad7e5140770aca
https://doi.org/10.20852/ntmsci.2019.383
https://doi.org/10.20852/ntmsci.2019.383
Publikováno v:
Journal of Mathematical Study. 52:394-424
In this work, we propose a multiscale approach for a nonstandard higher-order PDE based on the $p(\cdot)$-Kirchhoff energy. First, we consider a topological gradient approach for a semilinear case in order to detect important object of image. Then, w
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::cdc6025a76179ae7de16e5bf1a7d9b99
https://doi.org/10.4208/jms.v52n4.19.03
https://doi.org/10.4208/jms.v52n4.19.03
Publikováno v:
Nonlinear Analysis: Real World Applications. 47:251-271
We consider a class of nonstandard high-order PDEs models, based on the p ( ⋅ ) -Laplace operator with variable exponents, for image denoising and image inpainting problems. These models are obtained from the minimization of a family of anisotropic
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::1e1944891cff6dc77e3a13df7cf4c470
https://doi.org/10.1016/j.nonrwa.2018.10.013
https://doi.org/10.1016/j.nonrwa.2018.10.013
We study a Riemannian metric on the cone of symmetric positive-definite matrices obtained from the Hessian of the power potential function $(1-\det(X)^\beta)/\beta$. We give explicit expressions for the geodesics and distance function, under suitable
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::7ed44a03e2964a87587a85edf71936cf
Publikováno v:
Mathematics and Computers in Simulation. 144:138-152
In this paper we present an algorithm, that is based on computing approximate greatest common divisors (GCD) of polynomials, for solving the problem of blind image deconvolution. Specifically, we design a specialized algorithm for computing the GCD o
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::670127d988f9a7d1056ec7eb47c6d73d
https://doi.org/10.1016/j.matcom.2017.07.008
https://doi.org/10.1016/j.matcom.2017.07.008
Publikováno v:
Mathematical Methods in the Applied Sciences. 40:3637-3650
We consider a fourth-order variational model, to solve the image inpainting problem, with the emphasis on the recovery of low-dimensional sets (edges and corners) and the curvature of the edges. The model permits also to perform simultaneously the re
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::4dd9358cf478457a3a7a783c7a84c594
https://doi.org/10.1002/mma.4250
https://doi.org/10.1002/mma.4250