Elementary Linear Algebra: Applications Version, USED-Good, Anton, Howard,Rorres

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ISBN
9781118434413
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Product Identifiers

Publisher
Wiley & Sons, Incorporated, John
ISBN-10
1118434412
ISBN-13
9781118434413
eBay Product ID (ePID)
203574736

Product Key Features

Number of Pages
800 Pages
Publication Name
Elementary Linear Algebra : Applications Version
Language
English
Subject
Algebra / Linear
Publication Year
2013
Type
Textbook
Author
Howard Anton, Chris Rorres
Subject Area
Mathematics
Format
Hardcover

Dimensions

Item Height
1.2 in
Item Weight
57.7 Oz
Item Length
10.2 in
Item Width
8.8 in

Additional Product Features

Edition Number
11
Intended Audience
College Audience
Dewey Edition
22
Dewey Decimal
512/.5
Table Of Content
C H A P T E R 1 Systems of Linear Equations andMatrices 1.1 Introduction to Systems of Linear Equations 1.2 Gaussian Elimination 1.3 Matrices and Matrix Operations 1.4 Inverses; Algebraic Properties of Matrices 1.5 Elementary Matrices and a Method for Finding A ?1 1.6 More on Linear Systems and Invertible Matrices 1.7 Diagonal, Triangular, and Symmetric Matrices 1.8 Matrix Transformations 1.9 Applications of Linear Systems ? Network Analysis (Traffic Flow) ? Electrical Circuits ? Balancing Chemical Equations ? Polynomial Interpolation 1.10 Application: Leontief Input-Output Models C H A P T E R 2 Determinants 2.1 Determinants by Cofactor Expansion 2.2 Evaluating Determinants by Row Reduction 2.3 Properties of Determinants; Cramer?s Rule C H A P T E R 3 Euclidean Vector Spaces 3.1 Vectors in 2-Space, 3-Space, and n -Space 3.2 Norm, Dot Product, and Distance in R n 3.3 Orthogonality 3.4 The Geometry of Linear Systems 3.5 Cross Product C H A P T E R 4 General Vector Spaces 4.1 Real Vector Spaces 4.2 Subspaces 4.3 Linear Independence 4.4 Coordinates and Basis 4.5 Dimension 4.6 Change of Basis 4.7 Row Space, Column Space, and Null Space 4.8 Rank, Nullity, and the Fundamental Matrix Spaces 4.9 Basic Matrix Transformations in R 2 and R 3 4.10 Properties of Matrix Transformations 4.11 Application: Geometry of Matrix Operators on R 2 C H A P T E R 5 Eigenvalues and Eigenvectors 5.1 Eigenvalues and Eigenvectors 5.2 Diagonalization 5.3 Complex Vector Spaces 5.4 Application: Differential Equations 5.5 Application: Dynamical Systems and Markov Chains C H A P T E R 6 Inner Product Spaces 6.1 Inner Products 6.2 Angle and Orthogonality in Inner Product Spaces 6.3 Gram?Schmidt Process; QR -Decomposition 6.4 Best Approximation; Least Squares 6.5 Application: Mathematical Modeling Using LeastSquares 6.6 Application: Function Approximation; FourierSeries C H A P T E R 7 Diagonalization and Quadratic Forms 7.1 Orthogonal Matrices 7.2 Orthogonal Diagonalization 7.3 Quadratic Forms 7.4 Optimization Using Quadratic Forms 7.5 Hermitian, Unitary, and Normal Matrices C H A P T E R 8 General Linear Transformations 8.1 General Linear Transformation 8.2 Compositions and Inverse Transformations 8.3 Isomorphism 8.4 Matrices for General Linear Transformations 8.5 Similarity C H A P T E R 9 Numerical Methods 9.1 LU -Decompositions 9.2 The Power Method 9.3 Comparison of Procedures for Solving Linear Systems 9.4 Singular Value Decomposition 9.5 Application: Data Compression Using Singular ValueDecomposition C H A PT E R 10 Applications of Linear Algebra 10.1 Constructing Curves and Surfaces Through SpecifiedPoints 10.2 The Earliest Applications of Linear Algebra 10.3 Cubic Spline Interpolation 10.4 Markov Chains 10.5 Graph Theory 10.6 Games of Strategy 10.7 Leontief Economic Models 10.8 Forest Management 10.9 Computer Graphics 10.10 Equilibrium Temperature Distributions 10.11 Computed Tomography 10.12 Fractals 10.13 Chaos 10.14 Cryptography 10.15 Genetics 10.16 Age-Specific Population Growth 10.17 Harvesting of Animal Populations 10.18 A Least Squares Model for Human Hearing 10.19 Warps and Morphs 10.20 Internet Search Engines A P P E N D I X A Working with Proofs A P P E N D I X B Complex Numbers Answers to Exercises Index
Synopsis
Elementary Linear Algebra: Applications Version, 11th Edition gives an elementary treatment of linear algebra that is suitable for a first course for undergraduate students. The aim is to present the fundamentals of linear algebra in the clearest possible way; pedagogy is the main consideration. Calculus is not a prerequisite, but there are clearly labeled exercises and examples (which can be omitted without loss of continuity) for students who have studied calculus.

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