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Related lectures (25)
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Singular Value Decomposition: Applications and Interpretation
Explains the construction of U, verification of results, and interpretation of SVD in matrix decomposition.
Multivariate Statistics: Wishart and Hotelling T²
Explores the Wishart distribution, properties of Wishart matrices, and the Hotelling T² distribution, including the two-sample Hotelling T² statistic.
Characteristic Polynomials and Similar Matrices
Explores characteristic polynomials, similarity of matrices, and eigenvalues in linear transformations.
Linear Algebra: Reduction of Linear Application
Covers the reduction of a linear application and finding corresponding reduced forms and bases.
Eigenvalues and Minimal Polynomial
Explores eigenvalues and minimal polynomial, emphasizing their importance in linear algebra.
Linear Independence: The Wronskian Concept
Explains the Wronskian and its role in determining linear independence of solutions to differential equations.
Weak Formulation of Elliptic PDEs
Covers the weak formulation of elliptic partial differential equations and the uniqueness of solutions in Hilbert space.
Matrix Multiplication: Basics and Properties
Covers the basics of matrix multiplication, including properties and examples.
SVD: Singular Value Decomposition
Covers the concept of Singular Value Decomposition (SVD) for compressing information in matrices and images.
Convergence in Induced Matrix
Covers convergence in induced matrices and advection-diffusion phenomena.
