Skip to main content
Graph
Search
fr
en
Login
Search
All
Categories
Concepts
Courses
Lectures
MOOCs
People
Quizes
Exercises
Publications
Startups
Units
Show all results for
Home
Lecture
Diagonalizing Matrix A: VDV-1
Graph Chatbot
Related lectures (27)
Diagonalization of Linear Transformations
Explains the diagonalization of linear transformations using eigenvectors and eigenvalues to form a diagonal matrix.
Singular Values: Definitions and Properties
MOOC: Linear Algebra (Part 3)
Covers the concept of singular values in linear algebra and their properties, including diagonalization and practical examples.
Diagonalization: Step by Step
MOOC: Linear Algebra (Part 2)
Explains the step-by-step process of diagonalization for linear transformations on finite-dimensional vector spaces.
Diagonalization of Linear Transformations
Covers the diagonalization of linear transformations in R^3, exploring properties and examples.
Linear Algebra: Eigenvalues and Eigenvectors
Explores eigenvalues, eigenvectors, diagonalization, and spectral theorem in linear algebra.
Eigenvalue Problems: Methods and Applications
Explores eigenvalue problems, iterative methods, and their applications in quantum physics and network analysis.
Matrix Reduction: Part 1
Covers the reduction of a linear transformation in a 2-dimensional space to find a simpler matrix representation.
Matrix Computations: Eigenvalues and Eigenvectors
Delves into the complexity of matrix computations, focusing on eigenvalues and eigenvectors, algorithms, errors, and numerical stability.
Eigenvalue Problems: Methods and Applications
Explores eigenvalue problems, iterative methods, convergence properties, and applications in computational physics.
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.
Matrix Diagonalization: Spectral Theorem
Log in to Mediaspace to watch this video
Covers the process of diagonalizing matrices, focusing on symmetric matrices and the spectral theorem.
Diagonalization of Matrices
Log in to Mediaspace to watch this video
Explains the diagonalization of matrices, criteria, and significance of distinct eigenvalues.
Diagonalization of Matrices: Theory and Examples
Log in to Mediaspace to watch this video
Covers the theory and examples of diagonalizing matrices, focusing on eigenvalues, eigenvectors, and linear independence.
Diagonalizable Matrices: Properties and Examples
Log in to Mediaspace to watch this video
Explores the properties and examples of diagonalizable matrices, emphasizing the relationship between eigenvectors and eigenvalues.
Characteristic Polynomials and Similar Matrices
Log in to Mediaspace to watch this video
Explores characteristic polynomials, similarity of matrices, and eigenvalues in linear transformations.
Symmetric Matrices: Diagonalization
Log in to Mediaspace to watch this video
Explores symmetric matrices, their diagonalization, and properties like eigenvalues and eigenvectors.
Diagonalization: Theory and Examples
Log in to Mediaspace to watch this video
Explores diagonalization of matrices through eigenvalues and eigenvectors, emphasizing distinct eigenvalues and their role in the diagonalization process.
Diagonalization of Matrices
Log in to Mediaspace to watch this video
Explores the diagonalization of matrices through eigenvalues and eigenvectors, emphasizing the importance of bases and subspaces.
Diagonalization: Criteria and Examples
Log in to Mediaspace to watch this video
Covers the criteria for diagonalizing a matrix and provides illustrative examples.
Diagonalization of Matrices
Log in to Mediaspace to watch this video
Explores the diagonalization of matrices through eigenvectors and eigenvalues.
Previous
Page 1 of 2
Next
