How do I calculate a given matrix n-th's power formula?
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I wish to calculate a given matrix n-th power. Suppose the matrix is 3x3 and cannot be diagonalized. I've read there is a method using Cayley-Hamilton theorem to expand the matrix as a linear combination of its lower powers. Even when I do that, I can't find a generalization formula for the matrix n-th power. Is there any mathematical tool I can use to generalize it? I wish to know for the general case, of course, but in this particular case I have:A³=4A²-5A+2I, with eigenvalues 1, 1, and 2.I've been for a lot of time in this problem, and can't find a way to solve it... It's from Apostol's Calculus book, volume 2, exercise 7.12-10.
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Answer:
If you have [math]A^3 = 4A^2 - 5A + 2I[/math], then multiply both sides by [math]A^n[/math] to get [math]A^{n+3} = 4A^{n+2} - 5A^{n+1} + 2A^n[/math] for any non-negative integer [math]n[/math]. This is a linear recurrence relation, whose characteristic polynomial is [math]\lambda ^3 = 4\lambda^2 - 5\lambda + 2[/math]. The roots of this characteristic polynomial are [math]\lambda = 1, 1, 2[/math]. Therefore, the solution to this recurrence relation is [math]A^n = (C_1 + C_2 n) \cdot 1^n + C_3 \cdot 2^n[/math] for some constant matrices [math]C_1, C_2, C_3[/math]. For [math]n = 0, 1, 2[/math], we get: [math]C_1 + C_3 = I[/math][math]C_1 + C_2 + 2C_3 = A[/math][math]C_1 + 2C_2 + 4C_3 = A^2[/math]Solving this system yields: [math]C_1 = 2A-A^2[/math][math]C_2 = -2I+3A-A^2[/math][math]C_3 = I-2A+A^2[/math]Plugging this in yields the formula: [math]A^n =[/math] [math](2^n-2n)I -[/math] [math](2^{n+1}-3n-2)A +[/math] [math](2^n-n-1)A^2[/math].This method can easily be applied to other matrices, assuming we know the eigenvalues.
Santhosh Karnik at Quora Visit the source
Other answers
You can write the matrix in Jordan normal form, then the exponentiation will become much easier. That is, you can find a transformation [math]P[/math] such that your matrix [math]A = P J P^{-1}[/math] where [math]J[/math] is a block diagonal matrix with all the eigenvalues of [math]A[/math] on the main diagonal, all other non-zero elements are equal to 1 and all these are on the superdiagonal (one above the main diagonal). Powers [math]J^n[/math] can be easily found by blockwise multiplication, since each block has a very simple form. Then you simply use the transformation [math]P[/math] to reconstruct [math]A^n[/math]. For details of how to construct [math]P[/math] check the web.
David Kahana
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