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Titlebook: Numerical Methods for Ordinary Differential Equations; Initial Value Proble David F. Griffiths,Desmond J. Higham Textbook 2010 Springer-Ver

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書(shū)目名稱(chēng)Numerical Methods for Ordinary Differential Equations
副標(biāo)題Initial Value Proble
編輯David F. Griffiths,Desmond J. Higham
視頻videohttp://file.papertrans.cn/670/669082/669082.mp4
概述Focuses on the analysis of numerical methods without losing sight of the practical nature of the subject.Covers topics traditionally treated in a first course, but also highlights new and emerging the
叢書(shū)名稱(chēng)Springer Undergraduate Mathematics Series
圖書(shū)封面Titlebook: Numerical Methods for Ordinary Differential Equations; Initial Value Proble David F. Griffiths,Desmond J. Higham Textbook 2010 Springer-Ver
描述.Numerical Methods for Ordinary Differential Equations is a self-contained introduction to a fundamental field of numerical analysis and scientific computation. Written for undergraduate students with a mathematical background, this book focuses on the analysis of numerical methods without losing sight of the practical nature of the subject...It covers the topics traditionally treated in a first course, but also highlights new and emerging themes. Chapters are broken down into `lecture‘ sized pieces, motivated and illustrated by numerous theoretical and computational examples...Over 200 exercises are provided and these are starred according to their degree of difficulty. Solutions to all exercises are available to authorized instructors...The book covers key foundation topics:..o Taylor series methods..o Runge--Kutta methods..o Linear multistep methods..o Convergence..o Stability..and a range of modern themes:..o Adaptive stepsize selection..o Long term dynamics..o Modified equations..o Geometric integration..o Stochastic differential equations..The prerequisite of a basic university-level calculus class is assumed, although appropriate background results are also summarized in app
出版日期Textbook 2010
關(guān)鍵詞Convergence; Linear Multistep; Mathematica; Ordinary Differential Equations; Runge-Kutta; Stability; calcu
版次1
doihttps://doi.org/10.1007/978-0-85729-148-6
isbn_softcover978-0-85729-147-9
isbn_ebook978-0-85729-148-6Series ISSN 1615-2085 Series E-ISSN 2197-4144
issn_series 1615-2085
copyrightSpringer-Verlag London Limited 2010
The information of publication is updating

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Adaptive Step Size Selection, is proportional to 1/. and the accuracy of the results is proportional to .., for a method of order .. Thus, halving . is expected to double. the amount of computational effort while reducing the error by a factor of 2. (more than an extra digit of accuracy if . > 3).
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Modified Equations,ods. This attention is now shifted to the numerical method (primarily LMMs) and we ask whether the numerically computed values might be closer to the solution of a modified differential equation than they are to the solution of the original differential equation. At first sight this may appear to in
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,Geometric Integration Part II—Hamiltonian Dynamics,s. As in the previous chapter our emphasis is on.– showing that methods must be carefully chosen if they are to possess the correct geometric property, and.– using the idea of modified equations to explain the qualitative behaviour of numerical methods.
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Stochastic Differential Equations,imentally, in which case they are subject to measurement errors. Or the simulation of an epidemic might require an educated guess for the initial number of infected individuals. More fundamentally, there may be microscopic effects that (a) we are not able or willing to account for directly, but (b)
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1615-2085 in a first course, but also highlights new and emerging the.Numerical Methods for Ordinary Differential Equations is a self-contained introduction to a fundamental field of numerical analysis and scientific computation. Written for undergraduate students with a mathematical background, this book fo
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