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274 CHAPTER 9 Eigenvalues, Diagonalization, and Special Matrices
THEOREM 9.3 Eigenvalues of Real Symmetric Matrices
The eigenvalues of a real symmetric matrix are real.
Proof By Lemma 9.1 (equation (9.2)), for any eigenvalue λ of A, with eigenvector E =
(e 1 ,··· ,e n ),
t
E AE
λ = t .
E E
As noted previously, the denominator is
n
t 2
E E = |e j |
j=1
and this is real. All we have to do is show that the numerator real, which we will do by showing
t
that E AE equals its complex conjugate. First, because elements of A are real, each equals its
t
own conjugate, so A = A. Further, because A is symmetric, A = A. Therefore
t t t
t
E AE = E AE = E AE = E AE.
But the last quantity is a 1 × 1 matrix, which equals its own transpose. Thus, continuing the last
equation,
t
t
t
t
t t
t
E AE = (E AE) = (E )A(E ) = E AE.
t
The last two equations together show that E AE is its own conjugate, hence is real, proving the
theorem.
If the eigenvalues of a real matrix are all real, then associated eigenvectors will have real
elements as well. In the case that A is also symmetric, we claim that eigenvectors associated
with distinct eigenvalues must be orthogonal.
THEOREM 9.4 Orthogonality of Eigenvectors
Let A be a real symmetric matrix. Then eigenvectors associated with distinct eigenvalues are
orthogonal.
Proof We can derive this result by a useful interplay between matrix and vector notation. Let
λ and μ be distinct eigenvalues of A, with eigenvectors, respectively,
⎛ ⎞ ⎛ ⎞
e 1 g 1
e 2 g 2
⎜ ⎟ ⎜ ⎟
E = ⎜ . ⎟ and G = ⎜ . ⎟.
⎜ ⎟
⎜ ⎟
.
.
⎝ . ⎠ ⎝ . ⎠
e n g n
We have seen that
t
E · G = e 1 g 1 + e 2 g 2 + ··· + e n g n = E G.
t
Now use the facts that AE = λE, AG = μG, and A = A to write
t
t
t
t
λE G = (AE) G = (E A )G
t
t
t
t
= (E A)G = E (AG) = E (μG) = μE G.
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October 14, 2010 14:49 THM/NEIL Page-274 27410_09_ch09_p267-294