Advanced Linear Algebra - Advanced Linear Algebra, Lecture 5.7: The norm of a linear map
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What you'll learn
Understand key concepts of vector spaces, including spanning, independence, and bases.
Analyze the role of eigenvalues, eigenvectors, and the spectral theorem in linear mappings.
Apply the Gram-Schmidt process and orthogonal projection in various contexts.
Evaluate the properties and applications of quadratic forms and spectral resolutions.
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.
Course webpage: http://www.math.clemson.edu/~macaule/math8530-online.html
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