| 书目名称 | Numerical Analysis: A Graduate Course | | 编辑 | David E. Stewart | | 视频video | | | 概述 | Combines theory and practice in an application-based approach.Presents accessible graduate-level text.Includes algorithms and examples in Matlab and Julia programming | | 丛书名称 | CMS/CAIMS Books in Mathematics | | 图书封面 |  | | 描述 | .This book aims to introduce graduate students to the many applications of numerical computation, explaining in detail both how and why the included methods work in practice. The text addresses numerical analysis as a middle ground between practice and theory, addressing both the abstract mathematical analysis and applied computation and programming models instrumental to the field. While the text uses pseudocode, Matlab and Julia codes are available online for students to use, and to demonstrate implementation techniques. The textbook also emphasizes multivariate problems alongside single-variable problems and deals with topics in randomness, including stochastic differential equations and randomized algorithms, and topics in optimization and approximation relevant to machine learning. Ultimately, it seeks to clarify issues in numerical analysis in the context of applications, and presenting accessible methods to students in mathematics and data science. . | | 出版日期 | Textbook 2022 | | 关键词 | scientific computing; numerical analysis; numerical linear algebra; approximation theory; numerical diff | | 版次 | 1 | | doi | https://doi.org/10.1007/978-3-031-08121-7 | | isbn_softcover | 978-3-031-08123-1 | | isbn_ebook | 978-3-031-08121-7Series ISSN 2730-650X Series E-ISSN 2730-6518 | | issn_series | 2730-650X | | copyright | The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerl |
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发表于 2025-3-21 17:22:50
