Buch, Englisch, Band 19, 600 Seiten, Previously published in hardcover, Format (B × H): 155 mm x 235 mm, Gewicht: 937 g
Vol. II - Eigenvalues and Optimization
Buch, Englisch, Band 19, 600 Seiten, Previously published in hardcover, Format (B × H): 155 mm x 235 mm, Gewicht: 937 g
Reihe: Texts in Computational Science and Engineering
ISBN: 978-3-030-09871-1
Verlag: Springer International Publishing
This is the second of three volumes providing a comprehensive presentation of the fundamentals of scientific computing. This volume discusses more advanced topics than volume one, and is largely not a prerequisite for volume three. 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 49 examples, 110 exercises, 66 algorithms, 24 interactive JavaScript programs, 77 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 LAPACK, GSLIB and MATLAB.
This book could be used for a second course innumerical 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.
Zielgruppe
Graduate
Autoren/Hrsg.
Fachgebiete
- Mathematik | Informatik Mathematik Mathematische Analysis Differentialrechnungen und -gleichungen
- Mathematik | Informatik Mathematik Numerik und Wissenschaftliches Rechnen Angewandte Mathematik, Mathematische Modelle
- Mathematik | Informatik EDV | Informatik Angewandte Informatik Computeranwendungen in Wissenschaft & Technologie
- Mathematik | Informatik Mathematik Numerik und Wissenschaftliches Rechnen Numerische Mathematik
Weitere Infos & Material
1. Eigenvalues and Eigenvectors.- 2. Iterative Linear Algebra.- 3. Nonlinear Systems.- 4. Constrained Optimization.- References.- Author Index