Matrix Analysis and Applied Linear Algebra
[742/98%]C. D. Meyer
Chapter 1Linear Equations[38/84%]
Chapter 3Matrix Algebra[78/100%]
Section 3.3Linearity[4/100%]
Section 3.4Why Do It This Way[3/100%]
Section 3.5Matrix Multiplication[11/100%]
Section 3.7Matrix Inversion[12/100%]
Section 3.10The LU Factorization[10/100%]
Chapter 4Vector Spaces[129/100%]
Section 4.1Spaces and Subspaces[12/100%]
Section 4.3Linear Independence[15/100%]
Section 4.4Basis and Dimension[20/100%]
Section 4.5More about Rank[20/100%]
Section 4.6Classical Least Squares[10/100%]
Section 4.7Linear Transformations[19/100%]
Section 4.9Invariant Subspaces[8/100%]
Section 5.1Vector Norms[13/100%]
Section 5.2Matrix Norms[8/100%]
Section 5.3Inner-Product Spaces[9/100%]
Section 5.4Orthogonal Vectors[20/100%]
Section 5.5Gram-Schmidt Procedure[11/100%]
Section 5.7Orthogonal Reduction[8/100%]
Section 5.9Complementary Subspaces[20/100%]
Section 5.11Orthogonal Decomposition[14/100%]
Section 5.13Orthogonal Projection[22/100%]
Section 5.14Why Least Squares?[1/100%]
Section 5.15Angles between Subspaces[11/100%]
Chapter 6Determinants[48/100%]
Section 6.1Determinants[21/100%]
Section 7.5Normal Matrices[13/100%]
Section 7.8Jordan Form[13/100%]