Elementary linear algebra / Ron Larson, The Pennsylvania State University, The Behrend College.
By: Larson, Ron [author.].
Publisher: Boston, Massachusetts, USA : Cengage Learning, ©2017Copyright date: Boston, Massachusetts, USA : Cengage Learning, ©2017Edition: Eighth edition; student edition.Description: xiv, 398, 47 pages : illustrations (some color) ; 29 cm.Content type: text Media type: unmediated Carrier type: volumeISBN: 9781305658004 (hbk); 9781305953208 (looseleaf edition).Subject(s): Algebras, Linear | Linear algebraDDC classification: 512.5 L32 2017| Item type | Current location | Collection | Call number | Status | Date due | Barcode |
|---|---|---|---|---|---|---|
Books
|
College Library General Circulation Section | GC | GC 512.5 L32 2017 (Browse shelf) | Available | HNU000147 |
Browsing College Library Shelves , Shelving location: General Circulation Section , Collection code: GC Close shelf browser
| No cover image available | No cover image available | No cover image available | ||||||
| GC 512.13 F81 Algebra 1 Applications and Connections/ | GC 512.13 L32 2016 Algebra and trigonometry : | GC 512.13 L32 2016 Algebra and trigonometry : | GC 512.5 L32 2017 Elementary linear algebra / | GC 512.5 L45 2016 Linear algebra and its applications / | GC 512.5 L55 Linear algebra with applications/ | GC 512.5 L55 Linear Algebra with Applications/ |
Includes index.
1. SYSTEMS OF LINEAR EQUATIONS. Introduction to Systems of Equations. Gaussian Elimination and Gauss-Jordan Elimination. Applications of Systems of Linear Equations. 2. MATRICES. Operations with Matrices. Properties of Matrix Operations. The Inverse of a Matrix. Elementary Matrices. Markov Chains. Applications of Matrix Operations. 3. DETERMINANTS. The Determinant of a Matrix. Evaluation of a Determinant Using Elementary Operations. Properties of Determinants. Applications of Determinants. 4. VECTOR SPACES. Vectors in Rn. Vector Spaces. Subspaces of Vector Spaces. Spanning Sets and Linear Independence. Basis and Dimension. Rank of a Matrix and Systems of Linear Equations. Coordinates and Change of Basis. Applications of Vector Spaces. 5. INNER PRODUCT SPACES. Length and Dot Product in Rn. Inner Product Spaces. Orthogonal Bases: Gram-Schmidt Process. Mathematical Models and Least Squares Analysis. Applications of Inner Product Spaces. 6. LINEAR TRANSFORMATIONS. Introduction to Linear Transformations. The Kernel and Range of a Linear Transformation. Matrices for Linear Transformations. Transition Matrices and Similarity. Applications of Linear Transformations. 7. EIGENVALUES AND EIGENVECTORS. Eigenvalues and Eigenvectors. Diagonalization. Symmetric Matrices and Orthogonal Diagonalization. Applications of Eigenvalues and Eigenvectors. 8. COMPLEX VECTOR SPACES (online). Complex Numbers. Conjugates and Division of Complex Numbers. Polar Form and Demoivre's Theorem. Complex Vector Spaces and Inner Products. Unitary and Hermitian Spaces. 9. LINEAR PROGRAMMING (online). Systems of Linear Inequalities. Linear Programming Involving Two Variables. The Simplex Method: Maximization. The Simplex Method: Minimization. The Simplex Method: Mixed Constraints. 10. NUMERICAL METHODS (online). Gaussian Elimination with Partial Pivoting. Iterative Methods for Solving Linear Systems. Power Method for Approximating Eigenvalues. Applications of Numerical Methods
College of Education Bachelor of Secondary Education major in Mathematics
Text in English
There are no comments for this item.