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Home > Matrix & Vector calculators > Power Method for dominant eigenvalue example
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19. Power Method for finding dominant eigenvalue example
( Enter your problem )
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- Example `[[2,3],[4,10]]`
- Example `[[8,-6,2],[-6,7,-4],[2,-4,3]]`
- Example `[[1,1,1],[-1,-3,-3],[2,4,4]]`
- Example `[[2,3],[4,10]]`
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Other related methods
- Transforming matrix to Row Echelon Form
- Transforming matrix to Reduced Row Echelon Form
- Rank of matrix
- Characteristic polynomial of matrix
- Eigenvalues
- Eigenvectors (Eigenspace)
- Triangular Matrix
- LU decomposition using Gauss Elimination method of matrix
- LU decomposition using Doolittle's method of matrix
- LU decomposition using Crout's method of matrix
- Diagonal Matrix
- Cholesky Decomposition
- QR Decomposition (Gram Schmidt Method)
- QR Decomposition (Householder Method)
- LQ Decomposition
- Pivots
- Singular Value Decomposition (SVD)
- Moore-Penrose Pseudoinverse
- Power Method for dominant eigenvalue
- determinants using Sarrus Rule
- determinants using properties of determinants
- Row Space
- Column Space
- Null Space
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1. Example `[[2,3],[4,10]]`
Power Method for finding dominant eigenvalue ...
`[[2,3],[4,10]]`
Solution:
`1^(st)` Iteration
and by scaling we obtain the approximation
`2^(nd)` Iteration
and by scaling we obtain the approximation
`3^(rd)` Iteration
and by scaling we obtain the approximation
`4^(th)` Iteration
and by scaling we obtain the approximation
`:.` The dominant eigenvalue `lamda=11.29204`
and the dominant eigenvector is :
This material is intended as a summary. Use your textbook for detail explanation.
Any bug, improvement, feedback then
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