Normal view MARC view ISBD view

Elementary linear algebra : applications version / Howard Anton, Chris Rorres.

By: Anton, Howard.
Contributor(s): Rorres, Chris.
Material type: TextTextPublisher: New Jersey : Wiley, c2005Edition: 9th ed.Description: xv, 832p.: ill. (some col.) ; 26 cm.ISBN: 0471669598 (int.ed); 0471449024; 9780471449027.Subject(s): Algebras, Linear | Algebras, Linear -- Problems, exercises, etcDDC classification: 512.5 Online resources: WorldCat details
Contents:
Table of contents Chapter 1 Systems of Linear Equations and Matrices 1 -- 1.1 Introduction to Systems of Linear Equations 2 -- 1.2 Gaussian Elimination 8 -- 1.3 Matrices and Matrix Operations 23 -- 1.4 Inverses; Rules of Matrix Arithmetic 39 -- 1.5 Elementary Matrices and a Method for Finding A[superscript -1] 51 -- 1.6 Further Results on Systems of Equations and Invertibility 60 -- 1.7 Diagonal, Triangular, and Symmetric Matrices 68 -- Chapter 2 Determinants 83 -- 2.1 Determinants by Cofactor Expansion 84 -- 2.2 Evaluating Determinants by Row Reduction 96 -- 2.3 Properties of the Determinant Function 103 -- 2.4 A Combinatorial Approach to Determinants 111 -- Chapter 3 Vectors in 2-Space and 3-Space 123 -- 3.1 Introduction to Vectors (Geometric) 124 -- 3.2 Norm of a Vector; Vector Arithmetic 131 -- 3.3 Dot Product; Projections 136 -- 3.4 Cross Product 144 -- 3.5 Lines and Planes in 3-Space 156 -- Chapter 4 Euclidean Vector Spaces 167 -- 4.1 Euclidean n-Space 168 -- 4.2 Linear Transformations from R[superscript n] to R[superscript m] 181 -- 4.3 Properties of Linear Transformations from R[superscript n] to R[superscript m] 197 -- 4.4 Linear Transformations and Polynomials 210 -- Chapter 5 General Vector Spaces 221 -- 5.1 Real Vector Spaces 222 -- 5.2 Subspaces 229 -- 5.3 Linear Independence 240 -- 5.4 Basis and Dimension 250 -- 5.5 Row Space, Column Space, and Nullspace 266 -- 5.6 Rank and Nullity 279 -- Chapter 6 Inner Product Spaces 295 -- 6.1 Inner Products 296 -- 6.2 Angle and Orthogonality in Inner Product Spaces 307 -- 6.3 Orthonormal Bases; Gram-Schmidt Prodcess; QR-Decomposition 318 -- 6.4 Best Approximation; Least Squares 332 -- 6.5 Change of Basis 341 -- 6.6 Orthogonal Matrices 347 -- Chapter 7 Eigenvalues, Eigenvectors 359 -- 7.1 Eigenvalues and Eigenvectors 360 -- 7.2 Diagonalization 369 -- 7.3 Orthogonal Diagonalization 380 -- Chapter 8 Linear Transformations 389 -- 8.1 General Linear Transformations 390 -- 8.2 Kernel and Range 400 -- 8.3 Inverse Linear Transformations 407 -- 8.4 Matrices of General Linear Transformations 416 -- 8.5 Similarity 430 -- 8.6 Isomorphism 442 -- 9.1 Application to Differential Equations 452 -- 9.2 Geometry of Linear Operators on R[superscript 2] 458 -- 9.3 Least Squares Fitting to Data 468 -- 9.4 Approximation Problems; Fourier Series 474 -- 9.5 Quadratic Forms 479 -- 9.6 Diagonalizing Quadratic Forms; Conic Sections 487 -- 9.7 Quadric Surfaces 497 -- 9.8 Comparison of Procedures for Solving Linear Systems 502 -- 9.9 LU-Decompositions 511 -- Chapter 10 Complex Vector Spaces 521 -- 10.1 Complex Numbers 522 -- 10.2 Division of Complex Numbers 528 -- 10.3 Polar Form of a Complex Number 533 -- 10.4 Complex Vector Spaces 540 -- 10.5 Complex Inner Product Spaces 547 -- 10.6 Unitary Normal, and Hermitian Matrices 554 -- Chapter 11 Applications of Linear Algebra 567 -- 11.1 Constructing Curves and Surfaces through Specified Points 568 -- 11.2 Electrical Networks 574 -- 11.3 Geometric Linear Programming 578 -- 11.4 The Earliest Applications of Linear Algebra 590 -- 11.5 Cubic Spline Interpolation 597 -- 11.6 Markov Chains 608 -- 11.7 Graph Theory 619 -- 11.8 Games of Strategy 629 -- 11.9 Leontief Economic Models 639 -- 11.10 Forest Management 648 -- 11.11 Computer Graphics 657 -- 11.12 Equilibrium Temperature Distributions 665 -- 11.13 Computed Tomography 676 -- 11.14 Fractals 688 -- 11.15 Chaos 705 -- 11.16 Cryptography 719 -- 11.17 Genetics 732 -- 11.18 Age-Specific Population Growth 743 -- 11.19 Harvesting of Animal Populations 753 -- 11.20 A Least Squares Model for Human Hearing 762 -- 11.21 Warps and Morphs 768.
Summary: Summary: This classic treatment of linear algebra presents the fundamentals in the clearest possible way, examining basic ideas by means of computational examples and geometrical interpretation. It proceeds from familiar concepts to the unfamiliar, from the concrete to the abstract.
Tags from this library: No tags from this library for this title. Log in to add tags.
    Average rating: 0.0 (0 votes)
Item type Current location Collection Call number Copy number Status Date due Barcode Item holds Course reserves
Text Text EWU Library
Reserve Section
Non-fiction 512.5 ANE 2005 (Browse shelf) C-1 Not For Loan 16104
Text Text EWU Library
Reserve Section
Non-fiction 512.5 ANE 2005 (Browse shelf) C-2 Not For Loan 16105
Text Text EWU Library
Reserve Section
Non-fiction 512.5 ANE 2005 (Browse shelf) C-3 Not For Loan 16106
Text Text EWU Library
Circulation Section
Non-fiction 512.5 ANE 2005 (Browse shelf) C-4 Available 16107
Text Text EWU Library
Circulation Section
Non-fiction 512.5 ANE 2005 (Browse shelf) C-5 Available 16108
Text Text EWU Library
Circulation Section
Non-fiction 512.5 ANE 2005 (Browse shelf) C-6 Checked out 17/12/2019 18611
Text Text EWU Library
Circulation Section
Non-fiction 512.5 ANE 2005 (Browse shelf) C-7 Checked out 17/12/2019 18612
Text Text EWU Library
Circulation Section
Non-fiction 512.5 ANE 2005 (Browse shelf) C-8 Available 19576

Linear Algebra and Complex Variables

Total holds: 0

"Expanded version of Elementary linear algebra, ninth edition, by Howard Anton" - Preface.

ISBN printed on back cover: 0471449024

Table of contents Chapter 1 Systems of Linear Equations and Matrices 1 --
1.1 Introduction to Systems of Linear Equations 2 --
1.2 Gaussian Elimination 8 --
1.3 Matrices and Matrix Operations 23 --
1.4 Inverses; Rules of Matrix Arithmetic 39 --
1.5 Elementary Matrices and a Method for Finding A[superscript -1] 51 --
1.6 Further Results on Systems of Equations and Invertibility 60 --
1.7 Diagonal, Triangular, and Symmetric Matrices 68 --
Chapter 2 Determinants 83 --
2.1 Determinants by Cofactor Expansion 84 --
2.2 Evaluating Determinants by Row Reduction 96 --
2.3 Properties of the Determinant Function 103 --
2.4 A Combinatorial Approach to Determinants 111 --
Chapter 3 Vectors in 2-Space and 3-Space 123 --
3.1 Introduction to Vectors (Geometric) 124 --
3.2 Norm of a Vector; Vector Arithmetic 131 --
3.3 Dot Product; Projections 136 --
3.4 Cross Product 144 --
3.5 Lines and Planes in 3-Space 156 --
Chapter 4 Euclidean Vector Spaces 167 --
4.1 Euclidean n-Space 168 --
4.2 Linear Transformations from R[superscript n] to R[superscript m] 181 --
4.3 Properties of Linear Transformations from R[superscript n] to R[superscript m] 197 --
4.4 Linear Transformations and Polynomials 210 --
Chapter 5 General Vector Spaces 221 --
5.1 Real Vector Spaces 222 --
5.2 Subspaces 229 --
5.3 Linear Independence 240 --
5.4 Basis and Dimension 250 --
5.5 Row Space, Column Space, and Nullspace 266 --
5.6 Rank and Nullity 279 --
Chapter 6 Inner Product Spaces 295 --
6.1 Inner Products 296 --
6.2 Angle and Orthogonality in Inner Product Spaces 307 --
6.3 Orthonormal Bases; Gram-Schmidt Prodcess; QR-Decomposition 318 --
6.4 Best Approximation; Least Squares 332 --
6.5 Change of Basis 341 --
6.6 Orthogonal Matrices 347 --
Chapter 7 Eigenvalues, Eigenvectors 359 --
7.1 Eigenvalues and Eigenvectors 360 --
7.2 Diagonalization 369 --
7.3 Orthogonal Diagonalization 380 --
Chapter 8 Linear Transformations 389 --
8.1 General Linear Transformations 390 --
8.2 Kernel and Range 400 --
8.3 Inverse Linear Transformations 407 --
8.4 Matrices of General Linear Transformations 416 --
8.5 Similarity 430 --
8.6 Isomorphism 442 --
9.1 Application to Differential Equations 452 --
9.2 Geometry of Linear Operators on R[superscript 2] 458 --
9.3 Least Squares Fitting to Data 468 --
9.4 Approximation Problems; Fourier Series 474 --
9.5 Quadratic Forms 479 --
9.6 Diagonalizing Quadratic Forms; Conic Sections 487 --
9.7 Quadric Surfaces 497 --
9.8 Comparison of Procedures for Solving Linear Systems 502 --
9.9 LU-Decompositions 511 --
Chapter 10 Complex Vector Spaces 521 --
10.1 Complex Numbers 522 --
10.2 Division of Complex Numbers 528 --
10.3 Polar Form of a Complex Number 533 --
10.4 Complex Vector Spaces 540 --
10.5 Complex Inner Product Spaces 547 --
10.6 Unitary Normal, and Hermitian Matrices 554 --
Chapter 11 Applications of Linear Algebra 567 --
11.1 Constructing Curves and Surfaces through Specified Points 568 --
11.2 Electrical Networks 574 --
11.3 Geometric Linear Programming 578 --
11.4 The Earliest Applications of Linear Algebra 590 --
11.5 Cubic Spline Interpolation 597 --
11.6 Markov Chains 608 --
11.7 Graph Theory 619 --
11.8 Games of Strategy 629 --
11.9 Leontief Economic Models 639 --
11.10 Forest Management 648 --
11.11 Computer Graphics 657 --
11.12 Equilibrium Temperature Distributions 665 --
11.13 Computed Tomography 676 --
11.14 Fractals 688 --
11.15 Chaos 705 --
11.16 Cryptography 719 --
11.17 Genetics 732 --
11.18 Age-Specific Population Growth 743 --
11.19 Harvesting of Animal Populations 753 --
11.20 A Least Squares Model for Human Hearing 762 --
11.21 Warps and Morphs 768.

Summary:
This classic treatment of linear algebra presents the fundamentals in the clearest possible way, examining basic ideas by means of computational examples and geometrical interpretation. It proceeds from familiar concepts to the unfamiliar, from the concrete to the abstract.

Applied Physics & Electronics

There are no comments for this item.

Log in to your account to post a comment.

Library Home | Contacts | E-journals
Copyright @ 2011-2019 EWU Library
East West University