Linear Algebra II

Course Description

Vector Spaces. Basis and dimension. Matrices, row spaces, column spaces and null spaces. Rank and nullity. Inner product spaces. Inner products and orthonormal bases. Gram-Schmidt process. Least square problems and orthogonal matrices. Eigenvalues and eigenvectors. Diagonalization, orthogonal diagonalization. Linear transformations. Kernel and range. Inverse linear transformations. Similarity. Additional topics include quadratic forms, unitary, normal, Hermitian matrices, and canonical forms.


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