Eigenvalue/Eigenvector Proof for Matrix Polynomial p(A)

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Homework Statement



let p(x) = summation(from i=0 to k) aix^i

matrix polynomial for A is defined as p(A) = summation(i=0 up to k) aiA^i

Show that if (lambda, x) is an eigenpair of A then (p(lambda), x) is an eigenpair of p(A)

Homework Equations





The Attempt at a Solution



I pretty much have no idea where to start. I thought I could use Ax = lambda x like you would if you were proving that lambda^2 is an eigenvalue of A^2, etc, but I'm not sure how to get the p(A) bit?
 
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try multiplying the polynomial matrix form by the eignvector & see the results
 
here's some latex to help, click on it to see code

[tex]\sum_{i=0}^k a_i x^i[/tex]
 
Thanks, I'm still not sure if I'm going about this the right way

so I've got

Use Ax = [tex]\lambda[/tex]x

for p(A), multiply both sides of matrix polynomial by eigenvector x

p(A)x =
[tex] \sum_{i=0}^k a_i A^i [/tex] x

from the polynomial in the question, p(x) =
[tex] \sum_{i=0}^k a_i x^i [/tex]

let x = [tex]\lambda[/tex]

p([tex]\lambda[/tex]) =
[tex] \sum_{i=0}^k a_i \lambda^i [/tex]

p(A)x = [tex] \sum_{i=0}^k a_i \lambda^i [/tex] x

p(A)x = p([tex]\lambda[/tex]x as required

but I'm not sure if I've really shown anything. how do i show that its the same x and [tex]\lambda[/tex] that belong to the matrix A?