For sophomore-level or junior/senior-level first courses in Linear Algebra; assumes a Calculus prerequisite.
This thorough and accessible text - from one of the leading figures in the use of technology in linear algebra - gives students a challenging and broad understanding of the subject. The author infuses key concepts with their modern practical applications to offer students examples of how mathematics is used in the real world. Each chapter contains integrated worked examples and chapter tests. The book stresses the important role geometry and visualization play in understanding linear algebra. This edition will continue to be packaged with the ancillary ATLAST computer exercise guide, as well as new MATLAB and Maple guides, which are also free in the package.
Auflage
Sprache
Verlagsort
Verlagsgruppe
Zielgruppe
Maße
Höhe: 234 mm
Breite: 178 mm
Dicke: 19 mm
Gewicht
ISBN-13
978-0-13-200306-3 (9780132003063)
Copyright in bibliographic data and cover images is held by Nielsen Book Services Limited or by the publishers or by their respective licensors: all rights reserved.
Schweitzer Klassifikation
1. Matrices and Systems of Equations.
Systems of Linear Equations. Row Echelon Form. Matrix Algebra. Elementary Matrices. Partitioned Matrices. Matlab Exercises. Chapter Test.
2. Determinants.
The Determinant of a Matrix. Properties of Determinants. Cramer's Rule. Matlab Exercises. Chapter Test.
3. Vector Spaces.
Definition and Examples. Subspaces. Linear Independence. Basis and Dimension. Change of Basis. Row Space and Column Space. Matlab Exercises. Chapter Test.
4. Linear Transformations.
Definition and Examples. Matrix Representations of Linear Transformations. Similarity. Matlab Exercises. Chapter Test.
5. Orthogonality.
The Scalar Product in Rn. Orthogonal Subspaces. Least Squares Problems. Inner Product Spaces. Orthonormal Sets. The Gram-Schmidt Orthogonalization Process. Orthogonal Polynomials. Matlab Exercises. Chapter Test.
6. Eigenvalues.
Eigenvalues and Eigenvectors. Systems of Linear Differential Equations. Diagonalization. Hermitian Matrices. The Singular Value Decomposition. Quadratic Forms. Positive Definite Matrices. Nonnegative Matrices. Matlab Exercises. Chapter Test.
7. Numerical Linear Algebra.
Floating-Point Numbers. Gaussian Elimination. Pivoting Strategies. Matrix Norms and Condition Numbers. Orthogonal Transformations. The Eigenvalue Problem. Least Squares Problems. Matlab Exercises. Chapter Test.
8. Iterative Methods. On the website, as pdfs.
9. Jordan Canonical Form. On the website, as pdfs.
Appendix: MATLAB.
Bibliography.
Answers to Selected Exercises.
Index.
