Advanced analysis II

Related lectures (31)

Page 3 of 4

Explores eigenvalues and eigenvectors of Markov chains, focusing on convergence rates and matrix properties.

Explores diagonalization in symmetric matrices, emphasizing orthogonality and orthonormal bases.

Covers the diagonalization of symmetric matrices, the spectral theorem, and the use of spectral decomposition.

Covers the concept of diagonalization of matrices through the study of eigenvectors and eigenvalues.

Explores stability in linear 2D systems, covering fixed points, vector fields, and phase portraits.

Explores transient and spatial growth in flow instabilities, dispersion relations, and necessary conditions for instability.

Covers the theory and examples of diagonalizing matrices, focusing on eigenvalues, eigenvectors, and linear independence.

Covers Canonical Correlation Analysis, a method to find relationships between two sets of variables.

Covers the analysis of local extrema and Hessians, focusing on the development of limit notations.

Explores eigenvalues and eigenvectors in matrices through examples and calculations.