Normal view MARC view ISBD view

Introduction to scientific computing and data analysis / Mark H. Holmes.

By: Holmes, Mark H.
Series: Texts in computational science and engineering: 13.Publisher: Switzerland : Springer International Publishing, 2016Description: xiv, 487 pages : illustrations (some color) ; 24 cm.Content type: text Media type: unmediated Carrier type: volumeISBN: 9783319302546; 331930254X.Subject(s): Science -- Data processing | Quantitative research | Quantitative research | Science -- Data processingDDC classification: 502.85
Contents:
Introduction to Scientific Computing -- Solving a Nonlinear Equation -- Matrix Equations -- Eigenvalue Problems -- Interpolation -- Numerical Integration -- Initial Value Problems -- Optimization -- Data Analysis -- Appendices.
Summary: Annotation This textbook provides and introduction to numerical computing and its applications in science and engineering. The topics covered include those usually found in an introductory course, as well as those that arise in data analysis. This includes optimisation and regression based methods using a singular value decomposition. The emphasis is on problem solving, and there are numerous exercises throughout the text concerning applications in engineering and science. The essential role of the mathematical theory underlying the methods is also considered, both for understanding how the method works, as well as how the error in the computation depends on the method being used.
List(s) this item appears in: 2019 New Titles | Data Analysis
Item type Current location Call number Status Date due Barcode Item holds
BOOK BOOK NCAR Library
Mesa Lab
Q183.9 .H636 2016 Available 50583020008250
Total holds: 0

Includes bibliographical references and index.

Introduction to Scientific Computing -- Solving a Nonlinear Equation -- Matrix Equations -- Eigenvalue Problems -- Interpolation -- Numerical Integration -- Initial Value Problems -- Optimization -- Data Analysis -- Appendices.

Annotation This textbook provides and introduction to numerical computing and its applications in science and engineering. The topics covered include those usually found in an introductory course, as well as those that arise in data analysis. This includes optimisation and regression based methods using a singular value decomposition. The emphasis is on problem solving, and there are numerous exercises throughout the text concerning applications in engineering and science. The essential role of the mathematical theory underlying the methods is also considered, both for understanding how the method works, as well as how the error in the computation depends on the method being used.

Questions? Email library@ucar.edu.

Not finding what you are looking for? InterLibrary Loan.