Linear AlgebraMatrix Representation Problem

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SUMMARY

The discussion focuses on solving linear algebra problems related to matrix representation, specifically using the transformation D=U-1AU to derive a diagonal matrix. The diagonal matrix obtained is D = [ -2 0 0; 0 3 0; 0 0 1 ]. Additionally, the participant seeks clarification on whether the method for part F involves the transformation S=U-1V and the equation B=SAS-1. The conversation highlights the importance of understanding linear transformations and their representation in terms of ordered bases.

PREREQUISITES
  • Understanding of linear transformations in vector spaces
  • Familiarity with matrix operations, specifically inversion and multiplication
  • Knowledge of diagonalization of matrices
  • Concept of ordered bases in linear algebra
NEXT STEPS
  • Study the process of diagonalization of matrices in linear algebra
  • Learn about linear transformations and their matrix representations
  • Explore the properties and applications of matrix inversion
  • Investigate the relationship between ordered bases and linear transformations
USEFUL FOR

Students preparing for linear algebra exams, educators teaching matrix representation, and anyone seeking to deepen their understanding of linear transformations and diagonalization techniques.

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Homework Statement


I'm practicing for my finals this coming week and I'm confused about these 2 problems.
Screen Shot 2011-12-04 at 9.43.11 PM.png

Screen Shot 2011-12-04 at 9.44.25 PM.png

Homework Equations


The Attempt at a Solution


For e). I followed my notes and came up with D=U-1AU..since its asking for some basis to standard basis. And once computed, its the diagonal matrix.

D=
[-2 0 0]
[0 3 0]
[0 0 1]
So am I doing it right?

For part F). I don't know if its exactly the same method as above or do I need to get S=U-1V then B=SAS-1

I'm confused with all this!
 
Physics news on Phys.org
You've cut off the critical information: what "L" is!

In general, you write a linear transformation, from vector space, V, to itself, as a matrix, in terms of an ordered basis, by applying that linear transformation to each basis vector in turn, writing the result as a linear combination of those basis vectors. The coefficients of each linear combination give a column of the matrix.
 

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