- Išsiųsime per 10–14 d.d.
/https://libri-media.knygos-static.lt/79634c36-66f6-4246-a481-26f3081d4ee0/2)
- Leidėjas: Springer
- Metai: 2025
- Puslapiai: 164
- ISBN-10: 3032006783
- ISBN-13: 9783032006783
- Formatas: 15.5 x 23.5 x 0.9 cm, minkšti viršeliai
- Kalba: Anglų
- Extra -15 % nuolaida šiai knygai su kodu: ENG15
Mathematical Modelling of the Human Brain II (el. knyga) (skaityta knyga) | knygos.lt
Atsiliepimai
Aprašymas
This open access book revolves around predictive mathematical modelling and simulation of brain multiphysics with an emphasis on cerebrospinal fluid flow and solute transport in and around the human brain. The book consists of 10 self-contained and relatively short chapters, each offering a rapid introduction to a key problem or topic, supported by open source software. Readers will gain insights into state-of-the-art mathematical tools and techniques for modelling and simulation of brain multiphysics ranging from classical finite element approaches, network-based modelling techniques and deep neural networks. The target audiences are researchers in applied mathematics, scientific computing, biophysics, bioengineering or computational neuroscience interested in a compact introduction to image-based computational modeling of brain multiphysics and cutting-edge available tools.
EXTRA 15 % nuolaida su kodu: ENG15
Akcija baigiasi už 2d.05:05:56
Nuolaidos kodas galioja perkant nuo 5 €. Nuolaidos nesumuojamos.
- Leidėjas: Springer
- Metai: 2025
- Puslapiai: 164
- ISBN-10: 3032006783
- ISBN-13: 9783032006783
- Formatas: 15.5 x 23.5 x 0.9 cm, minkšti viršeliai
- Kalba: Anglų
This open access book revolves around predictive mathematical modelling and simulation of brain multiphysics with an emphasis on cerebrospinal fluid flow and solute transport in and around the human brain. The book consists of 10 self-contained and relatively short chapters, each offering a rapid introduction to a key problem or topic, supported by open source software. Readers will gain insights into state-of-the-art mathematical tools and techniques for modelling and simulation of brain multiphysics ranging from classical finite element approaches, network-based modelling techniques and deep neural networks. The target audiences are researchers in applied mathematics, scientific computing, biophysics, bioengineering or computational neuroscience interested in a compact introduction to image-based computational modeling of brain multiphysics and cutting-edge available tools.
Atsiliepimai