Linear Algebra With Applications
Sixth Edition

by
Steven J. Leon

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Select a section: Section 1.1: Systems of Linear Equations Section 1.2: Row Echelon Form Section 1.3: Matrix Algebra Section 1.4 Elementary Matrices Section 1.5: Partitioned Matrices Section 2.1: The Determinant of a Matrix Section 2.2: Properties of Determinants Section 2.3: Cramer's Rule Section 3.1 Definition and Examples Section 3.2: Subspaces Section 3.3: Linear Independence Section 3.4: Basis and Dimension Section 3.5: Change of Basis Section 3.6: Row Space and Column Space Section 4.1: Linear Transformations: Definition and Examples Section 4.2: Matrix Representations of Linear Transformations Section 4.3: Similarity Section 5.1: The Scalar Product in Rn Section 5.2: Orthagonal Subspaces Section 5.3: Least Squares Problems Section 5.4: Inner Product Spaces Section 5.5: Orthonormal Sets Section 5.6: The Gram-Schmidt Orthogonalization Process Section 5.7: Orthogonal Polynomials Section 6.1: Eigenvalues and Eigenvectors Section 6.2: Systems of Linear Differential Equations Section 6.3: Diagonalization Section 6.4: Hermitian Matrices Section 6.5: The Singular Value Decomposition Section 6.6: Quadratic Forms Section 6.7: Positive Definite Matrices Section 6.8: Nonnegative Matrices Section 7.1: Floating-Point Numbers Section 7.2: Gaussian Elimination Section 7.3: Pivoting Strategies Section 7.4: Matrix Norms and Condition Numbers Section 7.5: Orthogonal Transformations Section 7.6: The Eigenvalue Problem Section 7.7: Least Squares Problems Chapter 8: Iterative Methods Chapter 9 : Canonical Forms