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Another Linear Algebra Proof

An eigenvector of a matrix A is a vector v such that

Av = cv

Where c is a constant (c is usually lambda, but for the sake of formatting on the forums I'm going to use c).

If A is invertible, that means we can write (I'm going to use A' to be A^-1, again for ease of formatting)

A'Av = A'cv (multiply by A' on the left side)
Iv = cA'v (scalars and vectors commute; A'A = I; also note that Iv = v)
A'v = 1/c v
A'v = kv, where k = 1/c

Therefore A and A' have the same eigenvectors, but the eigenvalues are inverted.
 
Another question for you guys... What book did you guys used? The text I am currently using is printed in like 1989... And its soo hard to follow. I am thinking of getting another linear algebra book to use as reference.
 
While we're on the subject...did any of yall ever use Paul Foerster's textbooks in HS? For Agebra 1 and 2, pre cal, and cal? Just wondering.
 
Linear Algebra Done Right - Sheldon Axler

This book is excellent; the exposition is clear and the proofs are clean. However, it does omit some topics like dual spaces, quotient spaces, and tensor products.
 
I have a friend who thinks that Tom Apostol is the best math textbook writer in the history of human civilization. He has a Linear Algebra text.

Edit: I used Elementary Linear Algebra by Howard Anton and it was tolerable, although I'm sure better texts exist.
 
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