filmov
tv
Advanced Linear Algebra, Lecture 5.7: The norm of a linear map
Показать описание
Advanced Linear Algebra, Lecture 5.7: The norm of a linear map
The set Hom(X,U) of linear maps from X to U is itself a vector space, and so we can ask how to put an inner product structure or a norm on it. There are numerous ways to do this, and we introduce two of them. The Frobenius norm arises from the inner product (A,B)=tr(B*A) and is independent of the inner product structure on X or U. The induced norm, defined by ||A|| = max ||Ax||/||x||, depends on both inner product structures. In the remainder of the lecture, we prove some basic properties about this norm, and show that ||A||=||A*||. We also show that the invertible maps form an open subset of Hom(X,U). We conclude with a general definition of a norm of a linear map.
The set Hom(X,U) of linear maps from X to U is itself a vector space, and so we can ask how to put an inner product structure or a norm on it. There are numerous ways to do this, and we introduce two of them. The Frobenius norm arises from the inner product (A,B)=tr(B*A) and is independent of the inner product structure on X or U. The induced norm, defined by ||A|| = max ||Ax||/||x||, depends on both inner product structures. In the remainder of the lecture, we prove some basic properties about this norm, and show that ||A||=||A*||. We also show that the invertible maps form an open subset of Hom(X,U). We conclude with a general definition of a norm of a linear map.
Advanced Linear Algebra, Lecture 5.7: The norm of a linear map
Advanced Linear Algebra - Lecture 7: The Dimension of a Vector Space
Advanced Linear Algebra 5: Change of Basis
Advanced Linear Algebra - Lecture 5: Bases
Advanced Linear Algebra 7: Properties of Linear Transformations
Advanced Linear Algebra 1: Vector Spaces & Subspaces
Advanced Linear Algebra 4: Dimension of a Vector Space
Advanced Linear Algebra, Lecture 7.1: Definiteness and indefiniteness
Memorization Trick for Graphing Functions Part 1 | Algebra Math Hack #shorts #math #school
Advanced Linear Algebra 20: Positive Definite & Positive Semidefinite Matrices
Linear transformations | Matrix transformations | Linear Algebra | Khan Academy
Advanced Linear Algebra - Lecture 10: The Standard Matrix of a Linear Transformation
Advanced Linear Algebra, Lecture 5.9: Complex inner product spaces
Advanced Linear Algebra 6: Linear Transformations
Advanced Linear Algebra 3: Bases
Linear Algebra 7 | Examples for Subspaces
The Hardest Math Test
The Big Picture of Linear Algebra
Advanced Linear Algebra - Lecture 9: Linear Transformations
Advanced Linear Algebra - Lecture 6: Coordinate Vectors
Advanced Algebra Ch 5 7 Part 1 Study Guide
Linear Algebra 7 | Examples for Subspaces [dark version]
Advanced Linear Algebra, Lecture 2.4: The four subspaces
06 - What is a Function in Math? (Learn Function Definition, Domain & Range in Algebra)
Комментарии