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Linear Algebra and Its Applications  무료배송

 
지은이 : Strang
출판사 : Thomson
판수 : 4 edition
페이지수 : 496
ISBN : 0534422004
예상출고일 : 입금확인후 2일 이내
주문수량 :
도서가격 : 43,000원 ( 무료배송 )
적립금 : 1,290 Point
     

 
With a highly applied and computational focus, this book combines the important underlying theory with examples from electrical engineering, computer science, physics, biology and economics. An expanded list of computer codes in an appendix and more computer-solvable exercises in the text reflect Strang?s interest in computational linear algebra. Many exercises appear in the sections and in the chapter reviews. Exercises are simple but instructive. --This text refers to an out of print or unavailable edition of this title.
Gilbert Strang is Professor of Mathematics at the Massachusetts Institute of Technology and an Honorary Fellow of Balliol College. He was an undergraduate at MIT and a Rhodes Scholar at Oxford. His doctorate was from UCLA and since then he has taught at MIT. He has been a Sloan Fellow and a Fairchild Scholar and is a Fellow of the American Academy of Arts and Sciences. Professor Strang has published a monograph with George Fix, "An Analysis of the Finite Element Method", and has authored six widely used textbooks. He served as President of SIAM during 1999 and 2000 and he is Chair of the U.S. National Committee on Mathematics for 2003-2004. --This text refers to an out of print or unavailable edition of this title.

1. MATRICES AND GAUSSIAN ELIMINATION.
1.1 Introduction.
1.2 The Geometry of Linear Equations.
1.3 An Example of Gaussian Elimination.
1.4 Matrix Notation and Matrix Multiplication.
1.5 Triangular Factors and Row Exchanges.
1.6 Inverses and Transposes.
1.7 Special Matrices and Applications.
Review Exercises.

2. VECTOR SPACES.
2.1 Vector Spaces and Subspaces.
2.2 Solving Ax=0 and Ax=b.
2.3 Linear Independence, Basis, and Dimension.
2.4 The Four Fundamental Subspaces.
2.5 Graphs and Networks
2.6 Linear Transformations.
Review Exercises.

3. ORTHOGONALITY.
3.1쟏rthogonal Vectors and쟔ubspaces.
3.2 Cosines쟞nd Projections onto Lines.
3.3 Projections and Linear Squares
3.4쟏rthogonal Bases and Gram-Schmidt
3.5쟕he Fast Fourier Transform.�
Review Exercises.

4. DETERMINANTS.
4.1 Introduction.
4.2 Properties of the Determinant.
4.3 Formulas for the Determinant.
4.4 Applications of Determinants.
Review Exercises.

5. EIGENVALUES AND EIGENVECTORS.
5.1 Introduction.
5.2 Diagonalization of a Matrix.
5.3 Difference Equations and the Powers Ak.
5.4 Differential Equations and� eAt.
5.5 Complex Matrices:
5.6쟔imilarity Transformations.
Review Exercises.

6. POSITIVE DEFINITE MATRICES.
6.1 Minima, Maxima, and Saddle Points.
6.2 Tests for Positive Definiteness.
6.3쟔ingular Value Decomposition.
6.4 Minimum Principles.
6.5 The Finite Element Method.

7. COMPUTATIONS WITH MATRICES.
7.1 Introduction.
7.2 The Norm and Condition Number.
7.3잺omputation of Eigenvalues.
7.4 Iterative Methods for Ax = b.

8. LINEAR PROGRAMMING AND GAME THEORY.
8.1 Linear Inequalities.
8.2 The Simplex Method.
8.3쟕he잻ual Programs.
8.4 Network Models.
8.5 Game Theory.

Appendix A: Computer Graphics.
Appendix B: The Jordan Form.
References.
Solutions to Selected Exercises.
Matrix Factorizations
Glossary
MATLAB teaching Codes
Index.
Linear Algebra in Nutshell


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