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Advanced Linear Algebra, Lecture 4.3: Generalized eigenvectors
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Advanced Linear Algebra - Advanced Linear Algebra, Lecture 4.3: Generalized eigenvectors

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 4.3: Generalized eigenvectors Throughout, assume that A:X→X is an endomorphism of an n-dimensional vector space, or equivalently, an n-by-n matrix, over an algebraically closed field K. Since the polynomial ring K[t] is a principal ideal domain (PID), every ideal is generated by a single element. This means that the set (ideal) of polynomials p(t) such that p(A)=0 contains only multiples of a single polynomial m(t), called the "minimal polynomial" of A. By the Cayley-Hamilton theorem, this divides the characteristic polynomial. When A has repeated eigenvalues and not a full set of eigenvectors, the minimal polynomial has repeated roots. In this case, the eigenvectors can be extended into a basis for X by including so-called "generalized eigenvectors". Ordinary eigenvectors are characterized by being in the nullspace of A-λI. Generalized eigenvectors are in the nullspace of (A-λI)^m for some positive integer m. We see several 2x2 and 3x3 examples in this lecture, and give a novel way to visualize the generalized eigenvectors. The proof of these being a basis will be done throughout several subsequent lectures. Course webpage: http://www.math.clemson.edu/~macaule/math8530-online.html

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