Deterministic, Stochastic, and Deep Learning Methods for Computational Electromagnetics

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Springer

Paru le : 2025-03-02

This book provides a well-balanced and comprehensive picture based on clear physics, solid mathematical formulation, and state-of-the-art useful numerical methods in deterministic, stochastic, deep neural network machine learning approaches for computer simulations of electromagnetic and transport p...
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À propos

Auteur

Éditeur

Collection
n.c

Parution
2025-03-02

Pages
620 pages

EAN papier
9789819600991

Auteur(s) du livre


Prof. Wei Cai is the Clements chair professor in Applied Mathematics at the Department of Mathematics at Southern Methodist University. He obtained his B.S. and M.S. in Mathematics from the University of Science and Technology of China (USTC) in 1982 and 1985, respectively, and his Ph.D. in Applied Mathematics at Brown University in 1989. Before he joined SMU in the fall of 2017, he was an assistant and then associate professor at the University of California at Santa Barbara during 1995–1996 and a full professor at the University of North Carolina after 1999. He has also conducted collaborative research at Peking University, USTC, Shanghai Jiao Tong University, and Fudan University. He works on fast machine learning, stochastic, and deterministic numerical methods for scientific computing applications, and was awarded the Feng Kang prize in scientific computing in 2005.

Caractéristiques détaillées - droits

EAN PDF
9789819601004
Prix
168,79 €
Nombre pages copiables
6
Nombre pages imprimables
62
Taille du fichier
9841 Ko
EAN EPUB
9789819601004
Prix
168,79 €
Nombre pages copiables
6
Nombre pages imprimables
62
Taille du fichier
43284 Ko

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