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Logarithm of a matrix
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Related lectures (30)
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Diagonalization: Eigenvectors and Eigenvalues
Covers the diagonalization of matrices using eigenvectors and eigenvalues.
Jordan decomposition
Explores the unique decomposition of matrices into diagonalizable and nilpotent parts, showcasing their properties and applications.
Symmetric Matrices and Eigenvectors
Covers the concept of symmetric matrices, orthogonal bases, and eigenvectors.
Matrix Functions: Theory and Computation
Covers the theory and computation of matrix functions, focusing on computing f(A) and particularly e^A, with special attention to the matrix exponential and common examples of matrix functions.
Non-Diagonalizable Case: Triple Eigenvalue
Explores the scenarios of a matrix with a triple eigenvalue and its basis representation in R^3.
Taylor Polynomials: Examples and Convergence
Covers examples of Taylor polynomials and discusses their convergence when approximating functions.
Matrix Exponential: Properties and Justifications
Covers the properties of the matrix exponential and its justification through the norm definition.
Linear Algebra: Main Theorem and Injectivity
Covers the main theorem of linear algebra and the conditions for injectivity.
Eigenvalues Reduction: Two Real Eigenvalues
Explores the reduction of a matrix based on its eigenvalues, focusing on the case of two real eigenvalues.
Ker A = Ker (ATA)
Explores the equality between Ker A and Ker (ATA) in linear algebra.
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