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Advanced Linear Algebra, Lecture 2.3: Algebra of linear mappings
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Advanced Linear Algebra - Advanced Linear Algebra, Lecture 2.3: Algebra of linear mappings

Unlock the Power of Vector Spaces: Master Advanced Linear Algebra with Professor Macauley. Dive deep into theory and applications, from eigenvectors to spectral theorems. Enhance your mathematical prowess and transform complex problems into elegant solutions.

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43 learners

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.

This course includes

  • 25.5 hours of video
  • Certificate of completion
  • Access on mobile and TV

Summary

Full Transcript

Advanced Linear Algebra, Lecture 2.3: Algebra of linear mappings This is somewhat of a "catch all" lecture where a number of important definitions about linear maps and basic results are given. It could have been given right after Lecture 1.1, where we originally defined linear maps, but it seems more appropriate to put in the section devoted to linear maps. The set of linear maps from X to U, denoted Hom(X,U), forms a vector space. If X=U, then they additionally define an algebra -- a vector space where we are also allowed to multiply vectors. Such linear maps are called endomorphisms, and the invertible ones form a subalgebra called the general linear group. These define similarity transformations, and an equivalence relation on Hom(X,X). We sprinkle some examples of these concepts and others throughout the lecture. Course webpage: http://www.math.clemson.edu/~macaule/math8530-online.html

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