Holmes, Mark H.
Introduction to Scientific Computing and Data Analysis [electronic resource] / by Mark H. Holmes. - XIV, 497 p. 177 illus., 138 illus. in color. online resource. - Texts in Computational Science and Engineering, 13 1611-0994 ; . - Texts in Computational Science and Engineering, 13 .
Introduction to Scientific Computing -- Solving a Nonlinear Equation -- Matrix Equations -- Eigenvalue Problems -- Interpolation -- Numerical Integration -- Initial Value Problems -- Optimization -- Data Analysis -- Appendices.
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 optimization 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. The MATLAB codes used to produce most of the figures and data tables in the text are available on the author’s website and SpringerLink.
9783319302560
10.1007/978-3-319-30256-0 doi
Computer science.
Mathematical optimization.
Differential equations, partial.
Computational Science and Engineering.
Optimization.
Partial Differential Equations.
QA71-90
004
Introduction to Scientific Computing and Data Analysis [electronic resource] / by Mark H. Holmes. - XIV, 497 p. 177 illus., 138 illus. in color. online resource. - Texts in Computational Science and Engineering, 13 1611-0994 ; . - Texts in Computational Science and Engineering, 13 .
Introduction to Scientific Computing -- Solving a Nonlinear Equation -- Matrix Equations -- Eigenvalue Problems -- Interpolation -- Numerical Integration -- Initial Value Problems -- Optimization -- Data Analysis -- Appendices.
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 optimization 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. The MATLAB codes used to produce most of the figures and data tables in the text are available on the author’s website and SpringerLink.
9783319302560
10.1007/978-3-319-30256-0 doi
Computer science.
Mathematical optimization.
Differential equations, partial.
Computational Science and Engineering.
Optimization.
Partial Differential Equations.
QA71-90
004
