Solving ordinary differential equations in Python (Record no. 33769)

000 -LEADER
fixed length control field a
008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION
fixed length control field 250306b xxu||||| |||| 00| 0 eng d
020 ## - INTERNATIONAL STANDARD BOOK NUMBER
International Standard Book Number 9783031467677
082 ## - DEWEY DECIMAL CLASSIFICATION NUMBER
Classification number 003.3
Item number SUN
100 ## - MAIN ENTRY--PERSONAL NAME
Personal name Sundnes, Joakim
245 ## - TITLE STATEMENT
Title Solving ordinary differential equations in Python
260 ## - PUBLICATION, DISTRIBUTION, ETC. (IMPRINT)
Name of publisher, distributor, etc Springer,
Date of publication, distribution, etc 2024
Place of publication, distribution, etc Cham :
300 ## - PHYSICAL DESCRIPTION
Extent xii, 114 p. ;
Other physical details ill.,
Dimensions 24 cm
365 ## - TRADE PRICE
Price amount 39.99
Price type code $
Unit of pricing 89.70
490 ## - SERIES STATEMENT
Series statement Simula SpringerBriefs on computing,
Volume number/sequential designation 2512-1685 ; v.15
504 ## - BIBLIOGRAPHY, ETC. NOTE
Bibliography, etc Includes bibliographical references and index.
520 ## - SUMMARY, ETC.
Summary, etc This open access volume explains the foundations of modern solvers for ordinary differential equations (ODEs). Formulating and solving ODEs is an essential part of mathematical modeling and computational science, and numerous solvers are available in commercial and open source software. However, no single ODE solver is the best choice for every single problem, and choosing the right solver requires fundamental insight into how the solvers work. This book will provide exactly that insight, to enable students and researchers to select the right solver for any ODE problem of interest, or implement their own solvers if needed. The presentation is compact and accessible, and focuses on the large and widely used class of solvers known as Runge-Kutta methods. Explicit and implicit methods are motivated and explained, as well as methods for error control and automatic time step selection, and all the solvers are implemented as a class hierarchy in Python.
650 ## - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name as entry element Differential equations
Topical term or geographic name as entry element A-stable
Topical term or geographic name as entry element Backward Euler method
Topical term or geographic name as entry element Difference equations
Topical term or geographic name as entry element Hodgkin-Huxley model
Topical term or geographic name as entry element Implicit RK methods;
Topical term or geographic name as entry element Logistic growth
Topical term or geographic name as entry element Midpoint method
Topical term or geographic name as entry element Newton's method
Topical term or geographic name as entry element ODE systems
Topical term or geographic name as entry element Ordinary Differential Equations
Topical term or geographic name as entry element Runge-Kutta methods
Topical term or geographic name as entry element Taylor series
942 ## - ADDED ENTRY ELEMENTS (KOHA)
Source of classification or shelving scheme
Item type Books
Holdings
Withdrawn status Lost status Source of classification or shelving scheme Damaged status Not for loan Permanent location Current location Date acquired Source of acquisition Cost, normal purchase price Full call number Barcode Date last seen Koha item type
          DAU DAU 2025-02-21 KBD 3727.07 003.3 SUN 035235 2025-03-06 Books

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