Edward Barry Saff Arthur David Snider Saff Matrix Fundamentals

Matrix Fundamentals

von Edward Barry Saff Arthur David Snider

From Equation Solving to Signal Processing

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Beschreibung

Matrix Fundamentals introduces tools for working with matrices, their applications, and their significance in the broader context of linear algebra. Assuming no previous exposure to matrices, the first four chapters provide a foundation accessible to students with a basic knowledge of calculus, covering essential matrix methods used in various quantitative fields. The book formulates algorithms and discusses their practical implementation. Later chapters introduce more advanced topics, such as singular value decomposition, along with some modern applications. Emphasizing visualization and experimentation, this text is designed for undergraduate courses for students in STEM, as well as business, economics and social sciences.


Matrix Fundamentals introduces tools for working with matrices, their applications, and their significance in the broader context of linear algebra. Assuming no previous exposure to matrices, the first four chapters provide a foundation accessible to students with a basic knowledge of calculus, covering essential matrix methods used in various quantitative fields. The book formulates algorithms and discusses their practical implementation. Later chapters introduce more advanced topics, such as singular value decomposition, along with some modern applications. Emphasizing visualization and experimentation, this text is designed for undergraduate courses for students in STEM, as well as business, economics and social sciences.


Covers a range of topics and their applications, including singular value decompositions Provides guided explorations of advanced topics via group projects Includes advice on practical computing issues

Autor*in

Edward Barry Saff

Themen in »Matrix Fundamentals«

Gauss elimination LU factorization Rank of a Matrix Linear Transformation Rotation Matrices Matrix Exponential Jordan Normal Form Vector Spaces Eigenvalues Symmetric Matrices QR Factorization Schur Decomposition Positive Definite Matrices Orthogonal Matrices Least Squares

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Details

ISBN: 9783031972218
Verlag: Springer International Publishing
Erscheinung: 01.08.2025

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