Name: Mathematical Modelling of the Human Cardiovascular System: Data, Numerical Approximation, Clinical Applications (Cambridge Monographs on Applied and Computational Mathematics) (en Inglés)
Price: 434471.00 COP
Availability: InStock
Author: Alfio Quarteroni; Luca Dede'; Andrea Manzoni; Christian Vergara
ISBN: 9781108480390

portada Mathematical Modelling of the Human Cardiovascular System: Data, Numerical Approximation, Clinical Applications (Cambridge Monographs on Applied and Computational Mathematics) (en Inglés)

Mathematical Modelling of the Human Cardiovascular System: Data, Numerical Approximation, Clinical Applications (Cambridge Monographs on Applied and Computational Mathematics) (en Inglés)

Formato

Libro Físico

Editorial

Cambridge University Press

Autor

Alfio Quarteroni; Luca Dede'; Andrea Manzoni; Christian Vergara

Año

2019

Idioma

Inglés

N° páginas

290

Encuadernación

Tapa Dura

ISBN13

9781108480390

N° edición

Categorías

Matemáticas

Mathematical Modelling of the Human Cardiovascular System: Data, Numerical Approximation, Clinical Applications (Cambridge Monographs on Applied and Computational Mathematics) (en Inglés)

Alfio Quarteroni; Luca Dede'; Andrea Manzoni; Christian Vergara (Autor) · Cambridge University Press · Tapa Dura

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Reseña del libro "Mathematical Modelling of the Human Cardiovascular System: Data, Numerical Approximation, Clinical Applications (Cambridge Monographs on Applied and Computational Mathematics) (en Inglés)"

Mathematical and numerical modelling of the human cardiovascular system has attracted remarkable research interest due to its intrinsic mathematical difficulty and the increasing impact of cardiovascular diseases worldwide. This book addresses the two principal components of the cardiovascular system: arterial circulation and heart function. It systematically describes all aspects of the problem, stating the basic physical principles, analysing the associated mathematical models that comprise PDE and ODE systems, reviewing sound and efficient numerical methods for their approximation, and simulating both benchmark problems and clinically inspired problems. Mathematical modelling itself imposes tremendous challenges, due to the amazing complexity of the cardiovascular system and the need for computational methods that are stable, reliable and efficient. The final part is devoted to control and inverse problems, including parameter estimation, uncertainty quantiﬁcation and the development of reduced-order models that are important when solving problems with high complexity, which would otherwise be out of reach.