Description

Book Synopsis
This is the second edition of the best-selling introduction to linear algebra. Presupposing no knowledge beyond calculus, it provides a thorough treatment of all the basic concepts, such as vector space, linear transformation and inner product. The concept of a quotient space is introduced and related to solutions of linear system of equations, and a simplified treatment of Jordan normal form is given.Numerous applications of linear algebra are described, including systems of linear recurrence relations, systems of linear differential equations, Markov processes, and the Method of Least Squares. An entirely new chapter on linear programing introduces the reader to the simplex algorithm with emphasis on understanding the theory behind it.The book is addressed to students who wish to learn linear algebra, as well as to professionals who need to use the methods of the subject in their own fields.

Table of Contents
Matrix Algebra; Systems of Linear Equations; Determinants; Introduction to Vector Spaces; Basis and Dimension; Linear Transformations; Orthogonality in Vector Spaces; Eigenvectors and Eigenvalues; More Advanced Topics; Linear Programing.

Course In Linear Algebra With Applications, A

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    A Hardback by Derek J S Robinson

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      Book details

      Publisher World Scientific Publishing Co Pte Ltd
      Published 16 August 2006
      ISBN-13 9789812700230
      978-9812700230
      ISBN-10 9812700234

      Description

      Book Synopsis
      This is the second edition of the best-selling introduction to linear algebra. Presupposing no knowledge beyond calculus, it provides a thorough treatment of all the basic concepts, such as vector space, linear transformation and inner product. The concept of a quotient space is introduced and related to solutions of linear system of equations, and a simplified treatment of Jordan normal form is given.Numerous applications of linear algebra are described, including systems of linear recurrence relations, systems of linear differential equations, Markov processes, and the Method of Least Squares. An entirely new chapter on linear programing introduces the reader to the simplex algorithm with emphasis on understanding the theory behind it.The book is addressed to students who wish to learn linear algebra, as well as to professionals who need to use the methods of the subject in their own fields.

      Table of Contents
      Matrix Algebra; Systems of Linear Equations; Determinants; Introduction to Vector Spaces; Basis and Dimension; Linear Transformations; Orthogonality in Vector Spaces; Eigenvectors and Eigenvalues; More Advanced Topics; Linear Programing.

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