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Applied linear algebra and matrix an...

Shores, Thomas S.

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Applied linear algebra and matrix analysis

紀錄類型:	書目-電子資源 : Monograph/item
正題名/作者:	Applied linear algebra and matrix analysis/ by Thomas S. Shores.
作者:	Shores, Thomas S.
出版者:	Cham :Springer International Publishing : : 2018.,
面頁冊數:	xii, 479 p. :ill. (some col.), digital ;24 cm.
內容註:	1. Linear Systems of Equations -- 2. Matrix Algebra -- 3. Vector Spaces -- 4. Geometrical Aspects of Standard Spaces -- 5. The Eigenvalue Problem -- 6. Geometrical Aspects of Abstract Spaces.
Contained By:	Springer eBooks
標題:	Matrices. -
電子資源:	http://dx.doi.org/10.1007/978-3-319-74748-4
ISBN:	9783319747484

Applied linear algebra and matrix analysis
Shores, Thomas S.

Applied linear algebra and matrix analysis[electronic resource] /by Thomas S. Shores. - 2nd ed. - Cham :Springer International Publishing :2018. - xii, 479 p. :ill. (some col.), digital ;24 cm. - Undergraduate texts in mathematics,0172-6056. - Undergraduate texts in mathematics..

1. Linear Systems of Equations -- 2. Matrix Algebra -- 3. Vector Spaces -- 4. Geometrical Aspects of Standard Spaces -- 5. The Eigenvalue Problem -- 6. Geometrical Aspects of Abstract Spaces.

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.

ISBN: 9783319747484

Standard No.: 10.1007/978-3-319-74748-4doiSubjects--Topical Terms:

516894
Matrices.

LC Class. No.: QA184.2

Dewey Class. No.: 512.5

Applied linear algebra and matrix analysis
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520 $a 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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