Skip to main content
Graph
Search
fr
en
Login
Search
All
Categories
Concepts
Courses
Lectures
MOOCs
People
Practice
Publications
Startups
Units
Show all results for
Home
Lecture
Matrix Trace Properties
Graph Chatbot
Related lectures (23)
Previous
Page 2 of 3
Next
Diagonalization of Matrices
Explores the diagonalization of matrices through eigenvalues and eigenvectors, emphasizing the importance of bases and subspaces.
Convex Optimization: Linear Algebra Review
Provides a review of linear algebra concepts crucial for convex optimization, covering topics such as vector norms, eigenvalues, and positive semidefinite matrices.
Linear Transformations: Matrices and Applications
Covers linear transformations using matrices, focusing on linearity, image, and kernel.
Linear Algebra: Linear Dependence and Independence
Explores linear dependence and independence of vectors in geometric spaces.
Matrix Similarity and Diagonalization
Explores matrix similarity, diagonalization, characteristic polynomials, eigenvalues, and eigenvectors in linear algebra.
Orthogonal Matrices and Triangular Matrices
Explores properties of orthogonal and triangular matrices with linearly independent columns and their mathematical operations.
Eigenvalues and Eigenvectors Decomposition
Covers the decomposition of a matrix into its eigenvalues and eigenvectors, the orthogonality of eigenvectors, and the normalization of vectors.
Matrix Equations: Finding Free Variables
Explains how to find free variables in matrix equations and analyze characteristic polynomials.
Diagonalization of Matrices: Eigenvectors and Eigenvalues
Covers the concept of diagonalization of matrices through the study of eigenvectors and eigenvalues.
Linear Independence and Bases in Vector Spaces
Explains linear independence, bases, and dimension in vector spaces, including the importance of the order of vectors in a basis.