Applied linear algebra and matrix analysis
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TextSeries: Undergraduate texts in mathematicsPublication details: New York, NY : Springer Berlin Heidelberg, 2018. Edition: 2nd editionDescription: xii, 479 pages : illustrations (15 b/w illustrations, 30 illustrations in colour) ; 25 cmISBN: 9783319747477Subject(s): Algebra | Algebras, Linear | Matrix analytic methods | Gaussian elimination | Matrix theory | Gram-Schmidt algorithm | Vector spaces | Discrete dynamical systems | Matrix algebra | Google PageRank | Linear programmingDDC classification: 512.64 Online resources: Table of content | Reviews Summary: 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.
| Item type | Current library | Call number | Status | Date due | Barcode |
|---|---|---|---|---|---|
Book
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NISER LIBRARY | 512.64 SHO-A (Browse shelf(Opens below)) | Available | 25713 |
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| 512.64 SEW-C Computational methods of linear algebra | 512.64 SHA-S Solution manual for Lang's linear algebra | 512.64 SHE-L Linear algebra | 512.64 SHO-A Applied linear algebra and matrix analysis | 512.64 STR-L Linear algebra and its applications | 512.64 STR-L Linear algebra and its applications | 512.64 STR-L Linear algebra and its applications |
Includes bibliographical references (pages 469-470) and index.
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.
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