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Scientific computing.. Vol. III,. Ap...

Trangenstein, John A.

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Scientific computing.. Vol. III,. Approximation and integration

紀錄類型:	書目-電子資源 : Monograph/item
正題名/作者:	Scientific computing./ by John A. Trangenstein.
其他題名:	Approximation and integration
作者:	Trangenstein, John A.
出版者:	Cham :Springer International Publishing : : 2017.,
面頁冊數:	xxv, 592 p. :ill., digital ;24 cm.
內容註:	1. Interpolation and Approximation -- Differentiation and Integration -- Initial Value Problems -- Boundary Value Problems -- References -- Author Index.
Contained By:	Springer eBooks
標題:	Approximation theory. -
電子資源:	http://dx.doi.org/10.1007/978-3-319-69110-7
ISBN:	9783319691107

Scientific computing.. Vol. III,. Approximation and integration
Trangenstein, John A.

Scientific computing.Vol. III,Approximation and integration[electronic resource] /Approximation and integrationby John A. Trangenstein. - Cham :Springer International Publishing :2017. - xxv, 592 p. :ill., digital ;24 cm. - Texts in computational science and engineering,201611-0994 ;. - Texts in computational science and engineering ;20..

1. Interpolation and Approximation -- Differentiation and Integration -- Initial Value Problems -- Boundary Value Problems -- References -- Author Index.

This is the third of three volumes providing a comprehensive presentation of the fundamentals of scientific computing. This volume discusses topics that depend more on calculus than linear algebra, in order to prepare the reader for solving differential equations. This book and its companions show how to determine the quality of computational results, and how to measure the relative efficiency of competing methods. Readers learn how to determine the maximum attainable accuracy of algorithms, and how to select the best method for computing problems. This book also discusses programming in several languages, including C++, Fortran and MATLAB. There are 90 examples, 200 exercises, 36 algorithms, 40 interactive JavaScript programs, 91 references to software programs and 1 case study. Topics are introduced with goals, literature references and links to public software. There are descriptions of the current algorithms in GSLIB and MATLAB. This book could be used for a second course in numerical methods, for either upper level undergraduates or first year graduate students. Parts of the text could be used for specialized courses, such as nonlinear optimization or iterative linear algebra.

ISBN: 9783319691107

Standard No.: 10.1007/978-3-319-69110-7doiSubjects--Topical Terms:

628068
Approximation theory.

LC Class. No.: QA221

Dewey Class. No.: 511.4

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