1 code implementation • 17 Jul 2020 • Joonas Iivanainen, Antti J. Mäkinen, Rasmus Zetter, Koos C. J. Zevenhoven, Risto J. Ilmoniemi, Lauri Parkkonen
We describe a numerical implementation of the method; we model the conducting surface using a triangle mesh and discretize the stream function.
Computational Physics
1 code implementation • 20 May 2020 • Antti J. Mäkinen, Rasmus Zetter, Joonas Iivanainen, Koos C. J. Zevenhoven, Lauri Parkkonen, Risto J. Ilmoniemi
Surface currents provide a general way to model static magnetic fields in source-free volumes.
Computational Physics Applied Physics
1 code implementation • 20 May 2020 • Rasmus Zetter, Antti J. Mäkinen, Joonas Iivanainen, Koos C. J. Zevenhoven, Risto J. Ilmoniemi, Lauri Parkkonen
We present a novel open-source Python software package, bfieldtools, for magneto-quasistatic calculations with current densities on surfaces of arbitrary shape.
Computational Physics Applied Physics
1 code implementation • 14 Jul 2019 • Viktor Tóth, Lauri Parkkonen
To overcome these obstacles, we developed a novel class of SS methods, by training deep recurrent autoencoders for image-to-sound conversion.
no code implementations • 28 May 2018 • Ivan Zubarev, Rasmus Zetter, Hanna-Leena Halme, Lauri Parkkonen
Convolutional Neural Networks (CNN) outperform traditional classification methods in many domains.