Elementary Linear Algebra - 1st Edition - ISBN: 9780123484604, 9781483265179

Elementary Linear Algebra

1st Edition

Authors: Richard O. Hill
eBook ISBN: 9781483265179
Imprint: Academic Press
Published Date: 1st January 1986
Page Count: 416
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Elementary Linear Algebra reviews the elementary foundations of linear algebra in a student-oriented, highly readable way. The many examples and large number and variety of exercises in each section help the student learn and understand the material. The instructor is also given flexibility by allowing the presentation of a traditional introductory linear algebra course with varying emphasis on applications or numerical considerations. In addition, the instructor can tailor coverage of several topics.

Comprised of six chapters, this book first discusses Gaussian elimination and the algebra of matrices. Applications are interspersed throughout, and the problem of solving AX = B, where A is square and invertible, is tackled. The reader is then introduced to vector spaces and subspaces, linear independences, and dimension, along with rank, determinants, and the concept of inner product spaces. The final chapter deals with various topics that highlight the interaction between linear algebra and all the other branches of mathematics, including function theory, analysis, and the singular value decomposition and generalized inverses.

This monograph will be a useful resource for practitioners, instructors, and students taking elementary linear algebra.

Table of Contents


1 Introduction to Linear Equations and Matrices

1.1 Introduction to Linear Systems and Matrices

1.2 Gaussian Elimination

1.3 The Algebra of Matrices

1.4 Inverses and Elementary Matrices

1.5 Gaussian Elimination as a Matrix Factorization

1.6 Transposes, Symmetry, and Band Matrices; An Application

1.7 Numerical and Programming Considerations: Partial Pivoting, Overwriting Matrices, and Ill-Conditioned Systems

Review Exercises

2 Vector Spaces

2.1 Vectors in 2- and 3- Spaces

2.2 Euclidean n-Space

2.3 General Vector Spaces

2.4 Subspaces, Span, Null Spaces

2.5 Linear Independence

2.6 Basis and Dimension

2.7 The Fundamental Subspaces of a Matrix; Rank

2.8 An Application: Error-Correcting Codes

Review Exercises

3 Linear Transformations, Orthogonal Projections, and Least Squares

3.1 Matrices as Linear Transformations

3.2 Relationships Involving Inner Products

3.3 Least Squares and Orthogonal Projections

3.4 Orthogonal Bases and the Gram-Schmidt Process

3.5 Orthogonal Matrices, QR Decompositions, and Least Squares (Revisited)

3.6 Encoding the QR Decomposition—A Geometric Approach

Review Exercises

4 Eigenvectors and Eigenvalues

4.1 A Brief Introduction to Determinants

4.2 Eigenvalues and Eigenvectors

4.3 Diagonalization

4.4 Symmetric Matrices

4.5 An Application—Difference Equations: Fibonacci Sequences and Markov Processes

4.6 An Application—Differential Equations

4.7 An Application—Quadratic Forms

4.8 Solving the Eigenvalue Problem Numerically

Review Exercises

5 Dete


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© Academic Press 1986
Academic Press
eBook ISBN:

About the Author

Richard O. Hill

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