Elementary Linear Algebra: A Matrix approach
Publication details: Uttar Pradesh Pearson 2019 Edition: 2nd EditionSubject(s): MathematicsDDC classification: 512.897 Summary: Based on the recommendations of the linear algebra curriculum study Group, this introduction to linear algebra offers a matrix-oriented approach with more emphasis on problem solving and applications. Throughout the text, use of technology is encouraged. The focus is on matrix Arithmetic, systems of linear Equations, properties of Euclidean n-space, eigenvalues and eigenvectors, and orthogonality. Although matrix-oriented, the text provides a solid coverage of vector spaces. Contents: 1.Matrices, Vectors, and Systems of Linear Equations 2.Matrices and Linear Transformations 3. Determinants 4. Subspaces and their properties 5. Eigenvalues,eigenvectors and diagonalization 6. Orthogonality 7. Vector spaces| Item type | Home library | Call number | Materials specified | Status | Date due | Barcode |
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Parvatibai Chowgule College of Arts and Science, Margao Mathematics | 512.897 SPE.INS (Browse shelf(Opens below)) | Available | PCC-49473 |
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| 512.897 KAR.DAS Introduction to Linear Algebra Volume 2: Concepts, Theory and Applications | 512.897 LIP/LIP Linear Algebra | 512.897 ROS/Lin Linear Algebra | 512.897 SPE.INS Elementary Linear Algebra: A Matrix approach | 512.897 TOW/Gui Guide to Linear algebra | 512VAS/Mod Modern Algebra | 513.83KUM/Top Toplogy of Metric spaces |
Based on the recommendations of the linear algebra curriculum study Group, this introduction to linear algebra offers a matrix-oriented approach with more emphasis on problem solving and applications. Throughout the text, use of technology is encouraged. The focus is on matrix Arithmetic, systems of linear Equations, properties of Euclidean n-space, eigenvalues and eigenvectors, and orthogonality. Although matrix-oriented, the text provides a solid coverage of vector spaces.
Contents:
1.Matrices, Vectors, and Systems of Linear Equations
2.Matrices and Linear Transformations
3. Determinants
4. Subspaces and their properties
5. Eigenvalues,eigenvectors and diagonalization
6. Orthogonality
7. Vector spaces
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