Introduction to Scientific Computing and Data Analysis / by Mark H. Holmes.

Format:

Book

Author/Creator:

Holmes, Mark H.

Series:

Texts in Computational Science and Engineering, 2197-179X ; 13

Language:

English

Subjects (All):

Mathematics—Data processing.

Mathematical optimization.

Mathematical analysis.

Computational Science and Engineering.

Optimization.

Analysis.

Local Subjects:

Computational Science and Engineering.

Optimization.

Analysis.

Physical Description:

1 online resource (563 pages)

Edition:

2nd ed. 2023.

Place of Publication:

Cham : Springer International Publishing : Imprint: Springer, 2023.

Summary:

This textbook provides an 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 codes used for most of the computational examples in the text are available on GitHub. This new edition includes material necessary for an upper division course in computational linear algebra.

Contents:

Preface

Preface to Second Edition

Introduction to Scientific Computing

Solving a Nonlinear Equation

Matrix Equations

Eigenvalue Problems

Interpolation

Numerical Integration

Initial Value Problems

Optimization: Regression

Optimization: Descent Methods

Data Analysis

Taylor's Theorem

Vector and Matrix Summary

Answers

References

Index.

ISBN:

3-031-22430-2