Finding eigenvalues with the power series method

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SUMMARY

The discussion focuses on using the power method to approximate the dominant eigenvalues of the matrix A = [1,-5,5;-3,-1,3;1,-2,2]. The user begins with an initial vector V0 = [1;1;1] and calculates the first iteration u1 = A*V0 = [1;-1;1]. The main point of confusion arises regarding the normalization of the vector V1, specifically whether to divide by the largest magnitude component of u1 or its overall magnitude |u1|. The correct approach is to normalize by the largest magnitude component to ensure convergence towards the dominant eigenvalue.

PREREQUISITES
  • Understanding of matrix multiplication
  • Familiarity with the power method for eigenvalue approximation
  • Knowledge of eigenvalues and eigenvectors
  • Basic linear algebra concepts
NEXT STEPS
  • Study the power method for eigenvalue computation in detail
  • Learn about normalization techniques in vector calculations
  • Explore the concept of dominant eigenvalues and their significance
  • Investigate alternative methods for finding eigenvalues, such as the QR algorithm
USEFUL FOR

Students in linear algebra courses, mathematicians, and anyone interested in numerical methods for eigenvalue problems.

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Homework Statement


Consider the matrix [1,-5,5;-3,-1,3;1,-2,2]
Do four interations of the power method, beginning at [1,1,1] to approximate the dominant eigenvalues of A


Homework Equations


Matrix multiplication


The Attempt at a Solution



Okay my issue with this problem is this
I set V0 = [1;1;1],
Now I go to calculate u1
u1 = A*V0 = [1,-5,5;-3,-1,3;1,-2,2]*[1;1;1]=[1;-1;1], V1 = u1 / (?) and what value should i divide it by, which one has the largest magnitude, would it be -1, because I know that is unique, otherwise, is it 1?
Because I've tried both ways and I am not sure which way to go on this.
 
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You divide by the magnitude (i.e. length) of u1, or |u1|.
 

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