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pro vyhledávání: '"Pietro Dell'Acqua"'
The Alternating Direction Multipliers Method (ADMM) is a very popular algorithm for computing the solution of convex constrained minimization problems. Such problems are important from the application point of view, since they occur in many fields of
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::e511b61549e5cedd4f3e38a91e201d65
http://hdl.handle.net/11383/2102544
http://hdl.handle.net/11383/2102544
Autor:
Pietro Dell'Acqua
Publikováno v:
Advances in Computational Mathematics. 43:1283-1304
In recent years, several efforts were made in order to introduce boundary conditions for deblurring problems that allow to get accurate reconstructions. This resulted in the birth of Reflective, Anti-Reflective and Mean boundary conditions, which are
Publikováno v:
Computational Methods for Inverse Problems in Imaging ISBN: 9783030328818
Non-stationary regularizing preconditioners have recently been proposed for the acceleration of classical iterative methods for the solution of linear discrete ill-posed problems. This paper explores how these preconditioners can be combined with the
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::52c277ef8e7e3405899df7e3f0f90345
http://hdl.handle.net/11383/2085955
http://hdl.handle.net/11383/2085955
Autor:
Pietro Dell'Acqua, Claudio Estatico
Publikováno v:
Applied Numerical Mathematics. 99:121-136
An acceleration technique for multiplicative iterative methods, such as Lucy-Richardson and Image Space Reconstruction Algorithm, is presented. The technique is inspired by the Landweber method in Banach spaces and is based on the application of dual
Publikováno v:
IEEE Transactions on Intelligent Transportation Systems. 16:3393-3402
Traffic flow prediction is a fundamental functionality of intelligent transportation systems. After presenting the state of the art, we focus on nearest neighbor regression methods, which are data-driven algorithms that are effective yet simple to im
Autor:
Pietro Dell'Acqua
Publikováno v:
Signal, Image and Video Processing. 10:927-934
Image restoration problem is an important topic which appears in many different scientific areas. Several solving techniques are available, but generally in real applications, from which large-scale linear systems arise, the choice falls on iterative
Autor:
Antonio Cicone, Pietro Dell'Acqua
Publikováno v:
Journal of Computational and Applied Mathematics. 373:112248
Nonstationary and non-linear signals are ubiquitous in real life. Their decomposition and analysis is an important research topic of signal processing. Recently a new technique, called Iterative Filtering, has been developed with the goal of decompos
Publikováno v:
Journal of Computational and Applied Mathematics. 272:313-333
It is well known that iterative algorithms for image deblurring that involve the normal equations show usually a slow convergence. A variant of the normal equations which replaces the conjugate transpose A^H of the system matrix A with a new matrix i
Publikováno v:
Journal of Scientific Computing
Regularizing preconditioners for accelerating the convergence of iterative regularization methods without spoiling the quality of the approximated solution have been extensively investigated in the last twenty years. Several strategies have been prop
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::e2bfc592aa74302d8962f8d68c617ec9
http://hdl.handle.net/11567/858208
http://hdl.handle.net/11567/858208
Publikováno v:
Calcolo. 52:425-444
We analyse the practical efficiency of multi-iterative techniques for the numerical solution of graph-structured large linear systems. In particular we evaluate the effectiveness of several combinations of coarser-grid operators which preserve the gr