Applied Linear Algebra and Matrix Analysis
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Beschreibung
In its second edition, this textbook offers a fresh approach to matrix and linear algebra. Its blend of theory, computational exercises, and analytical writing projects is designed to highlight the interplay between these aspects of an application. This approach places special emphasis on linear algebra as an experimental science that provides tools for solving concrete problems.
The second edition’s revised text discusses applications of linear algebra like graph theory and network modeling methods used in Google’s PageRank algorithm. Other new materials include modeling examples of diffusive processes, linear programming, image processing, digital signal processing, and Fourier analysis. These topics are woven into the core material of Gaussian elimination and other matrix operations; eigenvalues, eigenvectors, and discrete dynamical systems; and the geometrical aspects of vector spaces.
Intended for a one-semester undergraduate course without a strict calculus prerequisite, Applied Linear Algebra and Matrix Analysis augments the key elements of linear algebra with a wide choice of optional sections. With the book’s selection of applications and platform-independent assignments, instructors can tailor the curriculum to suit specific interests and ensure students across various disciplines are equipped with the powerful tools of linear algebra.
Emphasizes linear algebra as an experimental science with a variety of modern applications Develops students’ analytical writing with report projects that require descriptive precision Explores applications of linear algebra to contemporary topics in technology, like Google PageRank Includes supplementary material: sn.pub/extras
Autor*in
Thomas S. Shores
Themen in »Applied Linear Algebra and Matrix Analysis«
Gaussian elimination singular value decomposition Gram-Schmidt algorithm orthogonal diagonalization vector spaces discrete dynamical systems matrix algebra operator norms applied linear algebra textbook Google PageRank linear programming digital signal processing diffusive processes matrix theory
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“The book could be the basis of a course in matrices and linear algebra, and certainly deserves a place in a university library.” (P. Macgregor, The Mathematical Gazette, Vol. 104 (560), July, 2020)
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