Description

Book Synopsis

Concise Introduction to Linear Algebra deals with the subject of linear algebra, covering vectors and linear systems, vector spaces, orthogonality, determinants, eigenvalues and eigenvectors, singular value decomposition. It adopts an efficient approach to lead students from vectors, matrices quickly into more advanced topics including, LU decomposition, orthogonal decomposition, Least squares solutions, Gram-Schmidt process, eigenvalues and eigenvectors, diagonalizability, spectral decomposition, positive definite matrix, quadratic forms, singular value decompositions and principal component analysis. This book is designed for onesemester teaching to undergraduate students.



Table of Contents

Vectors and linear systems. Solving linear systems. Vector spaces. Orthogonality. Determinants. Eigenvalues and Eigenvectors. Singular value decomposition.

Concise Introduction to Linear Algebra

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    A Hardback by Qingwen Hu

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      Book details

      Publisher CRC Press
      Published 9/21/2017 12:00:00 AM
      ISBN-13 9781138044494
      978-1138044494
      ISBN-10 1138044490
      Also in:
      Algebra Applied mathematics

      Description

      Book Synopsis

      Concise Introduction to Linear Algebra deals with the subject of linear algebra, covering vectors and linear systems, vector spaces, orthogonality, determinants, eigenvalues and eigenvectors, singular value decomposition. It adopts an efficient approach to lead students from vectors, matrices quickly into more advanced topics including, LU decomposition, orthogonal decomposition, Least squares solutions, Gram-Schmidt process, eigenvalues and eigenvectors, diagonalizability, spectral decomposition, positive definite matrix, quadratic forms, singular value decompositions and principal component analysis. This book is designed for onesemester teaching to undergraduate students.



      Table of Contents

      Vectors and linear systems. Solving linear systems. Vector spaces. Orthogonality. Determinants. Eigenvalues and Eigenvectors. Singular value decomposition.

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