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Numerical Approximation of Ordinary Differential Problems

- From Deterministic to Stochastic Numerical Methods
Af: Raffaele D'Ambrosio Engelsk Paperback

Numerical Approximation of Ordinary Differential Problems

- From Deterministic to Stochastic Numerical Methods
Af: Raffaele D'Ambrosio Engelsk Paperback
Tjek vores konkurrenters priser
This book is focused on the numerical discretization of ordinary differential equations (ODEs), under several perspectives. The attention is first conveyed to providing accurate numerical solutions of deterministic problems. Then, the presentation moves to a more modern vision of numerical approximation, oriented to reproducing qualitative properties of the continuous problem along the discretized dynamics over long times. The book finally performs some steps in the direction of stochastic differential equations (SDEs), with the intention of offering useful tools to generalize the techniques introduced for the numerical approximation of ODEs to the stochastic case, as well as of presenting numerical issues natively introduced for SDEs. The book is the result of an intense teaching experience as well as of the research carried out in the last decade by the author. It is both intended for students and instructors: for the students, this book is comprehensive and ratherself-contained; for the instructors, there is material for one or more monographic courses on ODEs and related topics. In this respect, the book can be followed in its designed path and includes motivational aspects, historical background, examples and a software programs, implemented in Matlab, that can be useful for the laboratory part of a course on numerical ODEs/SDEs. The book also contains the portraits of several pioneers in the numerical discretization of differential problems, useful to provide a framework to understand their contributes in the presented fields. Last, but not least, rigor joins readability in the book.
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This book is focused on the numerical discretization of ordinary differential equations (ODEs), under several perspectives. The attention is first conveyed to providing accurate numerical solutions of deterministic problems. Then, the presentation moves to a more modern vision of numerical approximation, oriented to reproducing qualitative properties of the continuous problem along the discretized dynamics over long times. The book finally performs some steps in the direction of stochastic differential equations (SDEs), with the intention of offering useful tools to generalize the techniques introduced for the numerical approximation of ODEs to the stochastic case, as well as of presenting numerical issues natively introduced for SDEs. The book is the result of an intense teaching experience as well as of the research carried out in the last decade by the author. It is both intended for students and instructors: for the students, this book is comprehensive and ratherself-contained; for the instructors, there is material for one or more monographic courses on ODEs and related topics. In this respect, the book can be followed in its designed path and includes motivational aspects, historical background, examples and a software programs, implemented in Matlab, that can be useful for the laboratory part of a course on numerical ODEs/SDEs. The book also contains the portraits of several pioneers in the numerical discretization of differential problems, useful to provide a framework to understand their contributes in the presented fields. Last, but not least, rigor joins readability in the book.
Produktdetaljer
Sprog: Engelsk
Sider: 385
ISBN-13: 9783031313424
Indbinding: Paperback
Udgave:
ISBN-10: 3031313429
Udg. Dato: 26 aug 2023
Længde: 0mm
Bredde: 155mm
Højde: 235mm
Forlag: Springer International Publishing AG
Oplagsdato: 26 aug 2023
Forfatter(e): Raffaele D'Ambrosio
Forfatter(e) Raffaele D'Ambrosio


Kategori Regning og matematisk analyse


ISBN-13 9783031313424


Sprog Engelsk


Indbinding Paperback


Sider 385


Udgave


Længde 0mm


Bredde 155mm


Højde 235mm


Udg. Dato 26 aug 2023


Oplagsdato 26 aug 2023


Forlag Springer International Publishing AG