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Code is changed on 22.07.2025, Now it also works for Complex Number.
For wrong or incomplete solution, please submit the feedback form.
So, I will try my best to improve it soon.
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Solution
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Solution provided by AtoZmath.com
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Inverse Power Method for finding dominant eigenvalue calculator
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1. `[[2,3],[5,4`invpowermethod`]]`
2. `[[1,6,1],[1,2,0],[0,0,3`invpowermethod`]]`
3. `[[1,2,0],[-2,1,2],[1,3,1`invpowermethod`]]`
4. `[[3,2],[1,4`invpowermethod`-1,1]]`
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Example1. Find Inverse Power Method for finding dominant eigenvalue ... `[[2,3],[5,4]]` `x_0` = Solution:1. Find `A^-1``=2 xx 4 - 3 xx 5` `=8 -15` `=-7` `"Now, "A^(-1)=1/|A| xx Adj(A)` | = | | `-0.5714` | `0.4286` | | | `0.7143` | `-0.2857` | |
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| `A^-1=` | | -0.5714 | 0.4286 | | | 0.7143 | -0.2857 | |
| `1^(st)` iteration :Multiply the matrix by the vector| `A^-1 x_0 =` | | -0.5714 | 0.4286 | | | 0.7143 | -0.2857 | |
| | | `=` | | Normalize the resulting vectorTo normalize, divide each element of vector by its largest absolute value, which is `0.4286` `2^(nd)` iteration :Repeat the multiplication| `A^-1 x_1 =` | | -0.5714 | 0.4286 | | | 0.7143 | -0.2857 | |
| | | `=` | | Normalize againThe largest absolute value is `0.619` `3^(rd)` iteration :Repeat the multiplication| `A^-1 x_2 =` | | -0.5714 | 0.4286 | | | 0.7143 | -0.2857 | |
| | | `=` | | Normalize againThe largest absolute value is `0.956` `4^(th)` iteration :Repeat the multiplication| `A^-1 x_3 =` | | -0.5714 | 0.4286 | | | 0.7143 | -0.2857 | |
| | | `=` | | Normalize againThe largest absolute value is `0.9869` `5^(th)` iteration :Repeat the multiplication| `A^-1 x_4 =` | | -0.5714 | 0.4286 | | | 0.7143 | -0.2857 | |
| | | `=` | | Normalize againThe largest absolute value is `0.999` `6^(th)` iteration :Repeat the multiplication| `A^-1 x_5 =` | | -0.5714 | 0.4286 | | | 0.7143 | -0.2857 | |
| | | `=` | | Normalize againThe largest absolute value is `0.9997` `7^(th)` iteration :Repeat the multiplication| `A^-1 x_6 =` | | -0.5714 | 0.4286 | | | 0.7143 | -0.2857 | |
| | | `=` | | Normalize againThe largest absolute value is `1` `:.` The dominant eigenvalue `lamda=1~=1` and the dominant eigenvector is :
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