Introduction to Scientific Computing and Data Analysis (Texts in Computational Science and Engineering, 13) - Softcover

Holmes, Mark H.

Softcover

ISBN 10: 3031224329 ISBN 13: 9783031224324

Publisher: Springer, 2024

Synopsis

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.

About this title

About the Author

Mark Holmes is a Professor at Rensselaer Polytechnic Institute.  His current research interests include mechanoreception and sleep-wake cycles. Professor Holmes has three published books in Springer's Texts in Applied Mathematics series: Introduction to Perturbation Methods, Introduction to the Foundations of Applied Mathematics, and Introduction to Numerical Methods in Differential Equations.

From the Back Cover

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.

Edition details

• Publisher: Springer
• Publication date: 2024
• Language: English
• ISBN 10: 3031224329
• ISBN 13: 9783031224324
• Binding: Paperback
• Edition number: 2
• Number of pages: 570