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Elementary linear algebra 11th ed

Elementary linear algebra 11th ed (8회 대출)

자료유형
단행본
개인저자
Anton, Howard.
서명 / 저자사항
Elementary linear algebra / Howard Anton, Professor Emeritus, Drexel University.
판사항
11th ed.
발행사항
Hoboken, NJ :   Wiley,   c2014.  
형태사항
xii, 525, 53 p. : ill. ; 27 cm.
ISBN
9781118473504 (cloth : acid-free paper) 1118473507 (cloth : acid-free paper)
일반주기
Includes index.  
내용주기
1. Systems of linear equations and matrices -- 2. Determinants -- 3. Euclidian vector spaces -- 4. General vector spaces -- 5. Eignvalues and eigenvectors -- 6. Inner product spaces -- 7. Diagonolization and quadratic forms -- 8. General linear transformations -- 9. Numerical methods.
일반주제명
Algebras, Linear --Textbooks.
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008 160127s2014 njua 001 0 eng d
010 ▼a 2013033541
020 ▼a 9781118473504 (cloth : acid-free paper)
020 ▼a 1118473507 (cloth : acid-free paper)
035 ▼a (KERIS)REF000017565277
040 ▼a DLC ▼b eng ▼c DLC ▼e rda ▼d DLC ▼d 211009
050 0 0 ▼a QA184.2 ▼b .A58 2013
082 0 0 ▼a 512/.5 ▼2 23
084 ▼a 512.5 ▼2 DDCK
090 ▼a 512.5 ▼b A634e11
100 1 ▼a Anton, Howard.
245 1 0 ▼a Elementary linear algebra / ▼c Howard Anton, Professor Emeritus, Drexel University.
250 ▼a 11th ed.
260 ▼a Hoboken, NJ : ▼b Wiley, ▼c c2014.
300 ▼a xii, 525, 53 p. : ▼b ill. ; ▼c 27 cm.
500 ▼a Includes index.
505 0 0 ▼g 1. ▼t Systems of linear equations and matrices -- ▼g 2. ▼t Determinants -- ▼g 3. ▼t Euclidian vector spaces -- ▼g 4. ▼t General vector spaces -- ▼g 5. ▼t Eignvalues and eigenvectors -- ▼g 6. ▼t Inner product spaces -- ▼g 7. ▼t Diagonolization and quadratic forms -- ▼g 8. ▼t General linear transformations -- ▼g 9. ▼t Numerical methods.
650 0 ▼a Algebras, Linear ▼v Textbooks.
945 ▼a KLPA

소장정보

No. 소장처 청구기호 등록번호 도서상태 반납예정일 예약 서비스
No. 1 소장처 과학도서관/Sci-Info(2층서고)/ 청구기호 512.5 A634e11 등록번호 121235472 도서상태 대출가능 반납예정일 예약 서비스 B M

컨텐츠정보

저자소개

HOWARD ANTON(지은이)

<알기쉬운 선형대수>

정보제공 : Aladin

목차

C H A P T E R 1 Systems of Linear Equations and Matrices

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 Rn

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 R2 and R3

4.10 Properties of Matrix Transformations

4.11 Application: Geometry of Matrix Operators on R2

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 Least Squares

6.6 Application: Function Approximation; Fourier Series

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 Value Decomposition

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

 


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