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Advanced Linear Algebra, Lecture 2.7: Change of basis
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Advanced Linear Algebra - Advanced Linear Algebra, Lecture 2.7: Change of basis

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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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

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Advanced Linear Algebra, Lecture 2.7: Change of basis If T is a linear map from X to U, and X≅R^n and U≅R^m, then we can define bijections B from X to R^n, and C from R^m, sending our bases of X and U to the standard bases. This defines a linear map N=CTB^{-1} from R^n to R^m, and hence a basis. If X=U, then this means that C=B, and N and T are similar. Along these lines, similar matrices can represent the same linear map but with respect to a different choice in basis. If B=P^{-1}AP, then P is a "change of basis matrix", and we see an explicit example of how to construct this in the 2x2 case, and the generalization to larger matrices should be apparent. Thought this lecture, we rely on commutative diagrams to illustrate these similarity transforms. Course webpage: http://www.math.clemson.edu/~macaule/math8530-online.html

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