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This lecture covers the concept of matrix similarity, where two matrices are considered similar if there exists an invertible matrix P such that B = PAP^-1. It also discusses the implications of matrix similarity on characteristic polynomials, eigenvalues, and eigenvectors. The process of diagonalizing a matrix is explained, along with methods for determining if a matrix is diagonalizable. Practical applications, such as calculating matrix powers and finding eigenvalues and eigenvectors of linear transformations, are also explored.
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