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Elementary Linear Algebra,

Edition 5

Editors: By Stephen Andrilli and David Hecker

Publication Date: 25 Feb 2016

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Elementary Linear Algebra, 5^th edition, by Stephen Andrilli and David Hecker, is a textbook for a beginning course in linear algebra for sophomore or junior mathematics majors. This text provides a solid introduction to both the computational and theoretical aspects of linear algebra. The textbook covers many important real-world applications of linear algebra, including graph theory, circuit theory, Markov chains, elementary coding theory, least-squares polynomials and least-squares solutions for inconsistent systems, differential equations, computer graphics and quadratic forms. Also, many computational techniques in linear algebra are presented, including iterative methods for solving linear systems, LDU Decomposition, the Power Method for finding eigenvalues, QR Decomposition, and Singular Value Decomposition and its usefulness in digital imaging.

The most unique feature of the text is that students are nurtured in the art of creating mathematical proofs using linear algebra as the underlying context. The text contains a large number of worked out examples, as well as more than 970 exercises (with over 2600 total questions) to give students practice in both the computational aspects of the course and in developing their proof-writing abilities. Every section of the text ends with a series of true/false questions carefully designed to test the students’ understanding of the material. In addition, each of the first seven chapters concludes with a thorough set of review exercises and additional true/false questions. Supplements to the text include an Instructor’s Manual with answers to all of the exercises in the text, and a Student Solutions Manual with detailed answers to the starred exercises in the text. Finally, there are seven additional web sections available on the book’s website to instructors who adopt the text.

Key Features

Builds a foundation for math majors in reading and writing elementary mathematical proofs as part of their intellectual/professional development to assist in later math courses
Presents each chapter as a self-contained and thoroughly explained modular unit.
Provides clearly written and concisely explained ancillary materials, including four appendices expanding on the core concepts of elementary linear algebra
Prepares students for future math courses by focusing on the conceptual and practical basics of proofs

About the author

By Stephen Andrilli, LaSalle University, Philadelphia, PA, USA and David Hecker, Professor, Mathematics Department, Saint Joseph's University, Philadelphia, PA, USA

Dedication
Preface for the Instructor
- Philosophy of the Text
- Major Changes for the Fifth Edition
- Plans for Coverage
- Prerequisite Chart for Later Sections
- Acknowledgments
Preface to the Student
A Light-Hearted Look at Linear Algebra Terms
Symbol Table
Computational & Numerical Techniques, Applications
Chapter 1: Vectors and Matrices
- Abstract
- 1.1 Fundamental Operations with Vectors
- 1.2 The Dot Product
- 1.3 An Introduction to Proof Techniques
- 1.4 Fundamental Operations with Matrices
- 1.5 Matrix Multiplication
- Review Exercises for Chapter 1
Chapter 2: Systems of Linear Equations
- Abstract
- 2.1 Solving Linear Systems Using Gaussian Elimination
- 2.2 Gauss-Jordan Row Reduction and Reduced Row Echelon Form
- 2.3 Equivalent Systems, Rank, and Row Space
- 2.4 Inverses of Matrices
- Review Exercises for Chapter 2
Chapter 3: Determinants and Eigenvalues
- Abstract
- 3.1 Introduction to Determinants
- 3.2 Determinants and Row Reduction
- 3.3 Further Properties of the Determinant
- 3.4 Eigenvalues and Diagonalization
- Review Exercises for Chapter 3
Chapter 4: Finite Dimensional Vector Spaces
- Abstract
- 4.1 Introduction to Vector Spaces
- 4.2 Subspaces
- 4.3 Span
- 4.4 Linear Independence
- 4.5 Basis and Dimension
- 4.6 Constructing Special Bases
- 4.7 Coordinatization
- Review Exercises for Chapter 4
Chapter 5: Linear Transformations
- Abstract
- 5.1 Introduction to Linear Transformations
- 5.2 The Matrix of a Linear Transformation
- 5.3 The Dimension Theorem
- 5.4 One-to-One and Onto Linear Transformations
- 5.5 Isomorphism
- 5.6 Diagonalization of Linear Operators
- Review Exercises for Chapter 5
Chapter 6: Orthogonality
- Abstract
- 6.1 Orthogonal Bases and the Gram-Schmidt Process
- 6.2 Orthogonal Complements
- 6.3 Orthogonal Diagonalization
Chapter 7: Complex Vector Spaces and General Inner Products
- Abstract
- 7.1 Complex n-Vectors and Matrices
- 7.2 Complex Eigenvalues and Complex Eigenvectors
- 7.3 Complex Vector Spaces
- 7.4 Orthogonality in

Chapter 8: Additional Applications

Abstract

8.1 Graph Theory

8.2 Ohm’s Law

8.3 Least-Squares Polynomials

8.4 Markov Chains

8.5 Hill Substitution: An Introduction to Coding Theory

8.6 Rotation of Axes for Conic Sections

8.7 Computer Graphics

8.8 Differential Equations

8.9 Least-Squares Solutions for Inconsistent Systems

8.10 Quadratic Forms

Chapter 9: Numerical Techniques

Abstract

9.1 Numerical Techniques for Solving Systems

9.2 LDU Decomposition

9.3 The Power Method for Finding Eigenvalues

9.4 QR Factorization

9.5 Singular Value Decomposition

Appendix A: Miscellaneous Proofs

Proof of Theorem 1.16, Part (1)

Proof of Theorem 2.6

Proof of Theorem 2.10

Proof of Theorem 3.3, Part (3), Case 2

Proof of Theorem 5.29

Proof of Theorem 6.19

Appendix B: Functions

Functions: Domain, Codomain, and Range

One-to-One and Onto Functions

Composition and Inverses of Functions

New Vocabulary

Highlights

Exercises for Appendix B

Appendix C: Complex Numbers

New Vocabulary

Highlights

Exercises for Appendix C

Appendix D: Elementary Matrices

Prerequisite: Section 2.4, Inverses of Matrices

Elementary Matrices

Representing a Row Operation as Multiplication by an Elementary Matrix

Inverses of Elementary Matrices

Using Elementary Matrices to Show Row Equivalence

Nonsingular Matrices Expressed as a Product of Elementary Matrices

New Vocabulary

Highlights

Exercises for Appendix D

Appendix E: Answers to Selected Exercises

Section 1.1 (p. 1–19)

Section 1.2 (p. 19–34)

Section 1.3 (p. 34–52)

Section 1.4 (p. 52–65)

Section 1.5 (p. 65–81)

Chapter 1 Review Exercises (p. 81–83)

Section 2.1 (p. 85–105)

Section 2.2 (p. 105–118)

Section 2.3 (p. 118–134)

Section 2.4 (p. 134–147)

Chapter 2 Review Exercises (p. 148–151)

Section 3.1 (p. 153–166)

Section 3.2 (p. 166–177)

Section 3.3 (p. 177–187)

Section 3.4 (p. 188–206)

Chapter 3 Review Exercises (p. 206–210)

Section 4.1 (p. 213–225)

Section 4.2 (p. 225–238)

Section 4.3 (p. 238–250)

Section 4.4 (p. 250–267)

Section 4.5 (p. 268–281)

Section 4.6 (p. 281–292)

Section 4.7 (p. 292–311)

Chapter 4 Review Exercises (p. 311–317)

Section 5.1 (p. 319–335)

Section 5.2 (p. 336–353)

Section 5.3 (p. 353–365)

Section 5.4 (p. 365–373)

Section 5.5 (p. 374–387)

Section 5.6 (p. 388–406)

Chapter 5 Review Exercises (p. 406–412)

Section 6.1 (p. 413–428)

Section 6.2 (p. 428–445)

Section 6.3 (p. 445–460)

Chapter 6 Review Exercises (p. 460–463)

Section 7.1 (p. 465–473)

Section 7.2 (p. 473–480)

Section 7.3 (p. 480–483)

Section 7.4 (p. 484–491)

Section 7.5 (p. 492–509)

Chapter 7 Review Exercises (p. 509–512)

Section 8.1 (p. 513–527)

Section 8.2 (p. 527–530)

Section 8.3 (p. 530–540)

Section 8.4 (p. 540–552)

Section 8.5 (p. 552–557)

Section 8.6 (p. 557–564)

Section 8.7 (p. 564–581)

Section 8.8 (p. 581–590)

Section 8.9 (p. 591–598)

Section 8.10 (p. 598–605)

Section 9.1 (p. 607–620)

Section 9.2 (p. 621–629)

Section 9.3 (p. 629–635)

Section 9.4 (p. 636–644)

Section 9.5 (p. 644–666)

Appendix B (p. 675–685)

Appendix C (p. 687–691)

Appendix D (p. 693–700)

Index

Inside Back Cover

Equivalent Conditions for Linearly Independent and Linearly Dependent Sets

Kernel Method (Finding a Basis for the Kernel of L)

Range Method (Finding a Basis for the Range of L)

Equivalent Conditions for One-to-One, Onto, and Isomorphism

Dimension Theorem

Gram-Schmidt Process

ISBN: 9780128008539

Page Count: 806

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Elementary Linear Algebra,

Editors: By Stephen Andrilli and David Hecker

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