Zobrazeno 1 - 10
of 88
pro vyhledávání: '"Zama, Fabiana"'
This study examines, in the framework of variational regularization methods, a multi-penalty regularization approach which builds upon the Uniform PENalty (UPEN) method, previously proposed by the authors for Nuclear Magnetic Resonance (NMR) data pro
Externí odkaz:
http://arxiv.org/abs/2309.14163
This paper proposes a new method for determining the simulation parameters of the Jiles-Atherton Model used to simulate the first magnetization curve and hysteresis loop in ferromagnetic materials. The Jiles-Atherton Model is an important tool in eng
Externí odkaz:
http://arxiv.org/abs/2308.14573
Autor:
Landi, Germana, Spinelli, Giovanni V., Zama, Fabiana, Martino, Delia Chillura, Conte, Pellegrino, Meo, Paolo Lo, Bortolotti, Villiam
Fast Field-Cycling Nuclear Magnetic Resonance relaxometry is a non-destructive technique to investigate molecular dynamics and structure of systems having a wide range of applications such as environment, biology, and food. Besides a considerable amo
Externí odkaz:
http://arxiv.org/abs/2208.04413
For Hamiltonian systems, simulation algorithms that exactly conserve numerical energy or pseudo-energy have seen extensive investigation. Most available methods either require the iterative solution of nonlinear algebraic equations at each time step,
Externí odkaz:
http://arxiv.org/abs/2206.12391
Autor:
Bortolotti, Villiam, Brizi, Leonardo, Landi, Germana, Nagmutdinova, Anastasiia, Zama, Fabiana
Accurate and efficient analysis of materials properties from Nuclear Magnetic Resonance (NMR) relaxation data requires robust and efficient inversion procedures. Despite the great variety of applications requiring to process two-dimensional NMR data
Externí odkaz:
http://arxiv.org/abs/2201.06504
Publikováno v:
In Mathematics and Computers in Simulation July 2024 221:210-221
A crucial issue in two-dimensional Nuclear Magnetic Resonance (NMR) is the speed and accuracy of the data inversion. This paper proposes a multi-penalty method with locally adapted regularization parameters for fast and accurate inversion of 2DNMR da
Externí odkaz:
http://arxiv.org/abs/2007.01268
Autor:
Piccolomini, Elena Loli, Zama, Fabiana
In this paper we propose a Susceptible-Infected-Exposed-Recovered-Dead (SEIRD) differential model for the analysis and forecast of the COVID-19 spread in some regions of Italy, using the data from the Italian Protezione Civile from February 24th 2020
Externí odkaz:
http://arxiv.org/abs/2003.09909
Publikováno v:
In Journal of Computational Physics 1 January 2023 472
In this paper we present a fast and efficient method for the reconstruction of Magnetic Resonance Images (MRI) from severely under-sampled data. From the Compressed Sensing theory we have mathematically modeled the problem as a constrained minimizati
Externí odkaz:
http://arxiv.org/abs/1711.11075