| 书目名称 | Introduction to Scientific Computing and Data Analysis |
| 编辑 | Mark H. Holmes |
| 视频video | |
| 概述 | Codes used for all of the computational examples are available on GitHub.Covers optimization methods, regression principal & independent component analysis & variational calculus.Problem solving & the |
| 丛书名称 | Texts in Computational Science and Engineering |
| 图书封面 |  |
| 描述 | 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.. |
| 出版日期 | Textbook 2023Latest edition |
| 关键词 | Scientific Computing; Data Analysis; Optimization; Interpolation; Nonlinear Equations; Numerical Linear A |
| 版次 | 2 |
| doi | https://doi.org/10.1007/978-3-031-22430-0 |
| isbn_softcover | 978-3-031-22432-4 |
| isbn_ebook | 978-3-031-22430-0Series ISSN 1611-0994 Series E-ISSN 2197-179X |
| issn_series | 1611-0994 |
| copyright | The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerl |
发表于 2025-3-21 17:23:49
