Description

Book Synopsis

The techniques of linear algebra are used extensively across the applied sciences, and in many different areas of algebra such as group theory, module theory, representation theory, ring theory, and Galois theory. Written by experienced researchers with a decades of teaching experience, Introduction to Linear Algebra is a clear and rigorous introductory text on this key topic for students of both applied sciences and pure mathematics.



Table of Contents
Linear Vector Spaces. Matrices. Determinants. Invertible Matrices. Linear Systems. LU Factorization. Linear Dependence and Independence. Bases and Dimension. Coordinates and Isomorphisms. Rank of a Matrix. Linear Mappings. Matrix Representation of Linear Mappings. Inner Products and Orthogonality. Linear Functionals. Eigenvalues and Eigenvectors. Normed Linear Spaces. Diagonalization. Singular Value Decomposition. Differential and Difference Systems. Least Squares Approximation. Quadratic Forms. Positive Definite Matrices. Moore–Penrose Inverse.Special Matrices.

An Introduction to Linear Algebra

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    A Hardback by Elena Cristina Flaut, Elena Cristina Flaut

    £999.99

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      Book details

      Publisher CRC Press
      Published 1/28/2017 12:07:00 AM
      ISBN-13 9781138626706
      978-1138626706
      ISBN-10 1138626708
      Also in:
      Algebra Applied mathematics Environmental science, engineering and technology

      Description

      Book Synopsis

      The techniques of linear algebra are used extensively across the applied sciences, and in many different areas of algebra such as group theory, module theory, representation theory, ring theory, and Galois theory. Written by experienced researchers with a decades of teaching experience, Introduction to Linear Algebra is a clear and rigorous introductory text on this key topic for students of both applied sciences and pure mathematics.



      Table of Contents
      Linear Vector Spaces. Matrices. Determinants. Invertible Matrices. Linear Systems. LU Factorization. Linear Dependence and Independence. Bases and Dimension. Coordinates and Isomorphisms. Rank of a Matrix. Linear Mappings. Matrix Representation of Linear Mappings. Inner Products and Orthogonality. Linear Functionals. Eigenvalues and Eigenvectors. Normed Linear Spaces. Diagonalization. Singular Value Decomposition. Differential and Difference Systems. Least Squares Approximation. Quadratic Forms. Positive Definite Matrices. Moore–Penrose Inverse.Special Matrices.

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