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Advanced Linear Algebra, Lecture 5.6: Isometries
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Advanced Linear Algebra - Advanced Linear Algebra, Lecture 5.6: Isometries

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 5.6: Isometries An isometry in a vector space is a map that preserves the norm, i.e., ||Ax-Ay||=||x-y|| for all vectors x and y. Examples include rotations, reflections, and translations. Given any isometry, we can compose it with a translation to get an isometry that fixes the zero vector. Such a map is said to be orthogonal. We show that such a map also preserves inner products, is linear, invertible, and its determinant is ±1, which can be thought of as "volume preserving". Finally, an isometry is characterized by the relation A*A=I, which in matrix form, means that the columns are an orthonormal basis. Course webpage: http://www.math.clemson.edu/~macaule/math8530-online.html

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