Numerical Analysis: A Graduate Course

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 mathematica...

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Detalles Bibliográficos
Autor principal: Stewart, David E. (-)
Formato: Libro electrónico
Idioma:Inglés
Publicado: Cham : Springer International Publishing 2022.
Edición:1st ed. 2022.
Colección:Springer eBooks.
CMS/CAIMS Books in Mathematics ; 4.
Acceso en línea:Conectar con la versión electrónica
Ver en Universidad de Navarra:https://innopac.unav.es/record=b47354124*spi
Descripción
Sumario: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. .
Descripción Física:1 recurso electrónico, XV, 632 páginas, 114 ilustraciones, 66 ilustraciones en color
Formato:Forma de acceso: World Wide Web.
ISBN:9783031081217