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# Linear Algebra Foundations #10 - Eigenvectors

# Linear Algebra Foundations #10 - Eigenvectors

bennattj + 0 comments Well this "notation" couldn't have been more confusing. For anyone else confused, this is what they are asking for:

The k_1 and k_2 (or both k_1's as they wrote it) are simply the fact that a multiple of an eigenvector is also an eigenvector.

merajmasuk + 1 comment What is actually k1 here?

octavianarsene + 0 comments k is the positive integer variable (consider it as a multiple)

Check this: https://www.safaribooksonline.com/library/view/linear-algebra-concepts/9781107484535/16_chapter-title-8.html

shubhamkr11 + 0 comments I could not understand the formula provided - v1 = k1 [+1 A ]T

kiner_shah + 1 comment Ans is -2 -1 right? I am getting WA!

sagarys49Asked to answer + 2 comments **Endorsed by kiner_shah**yes it is correct but you are not putting in the correct form type each solution in the seperate line.

you will ge tthe answer correctly.

kiner_shah + 0 comments Got it! Thnxx! :-)

sahmad39 + 1 comment Isn't there 2 eigenvectors? One for when lambda = -1 and one for lambda = -2? So like one is (-1,1) and the other is (-2,-1) ?

ryklin + 1 comment I got span[-1 1] for lambda -1 and span [-2 1] for lambda -2

I think in the lambda -2 case you might have made a mistake because row reduced echelon form of the matrix is: [1 1/2; 0 0]

Therefore if v1 == - 1/2*v2, you then multiply by -2 and you get [-2 1] as the solution for the vector v.

I double checked this solution.

Nonetheless, I have no idea how to enter this into the solution box!

thebick + 0 comments see what bennattj wrote: A and B fill the column vectors (1 A) and (1 B).

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