196 CHAPTER 11. MATRICES AND THE INNER PRODUCT

From the above explanation the columns of this matrix U are eigenvectors of unit lengthand in fact this is sufficient to obtain the matrix. After doing row operations and thennormalizing the vectors, you obtain 1 −4 13

−4 10 −413 −4 1



16

√6

13

√6

16

√6

=

√

62√

6√6

= 6

16

√6

13

√6

16

√6

 1 −4 13−4 10 −413 −4 1

 −

12

√2

012

√2

=

 6√

20

−6√

2

=−12

 −12

√2

012

√2

 1 −4 13−4 10 −413 −4 1



13

√3

− 13

√3

13

√3

=

 6√

3−6√

36√

3

= 18

13

√3

− 13

√3

13

√3

Thus the matrix of interest is

U =

16

√6 − 1

2

√2 1

3

√3

13

√6 0 − 1

3

√3

16

√6 1

2

√2 1

3

√3

Then 

16

√6 − 1

2

√2 1

3

√3

13

√6 0 − 1

3

√3

16

√6 1

2

√2 1

3

√3

T  1 −4 13

−4 10 −413 −4 1

 ·

16

√6 − 1

2

√2 1

3

√3

13

√6 0 − 1

3

√3

16

√6 1

2

√2 1

3

√3

=

 6 0 00 −12 00 0 18

11.5 DiagonalizationTheorem 11.4.7 is a special case of something known as diagonalization.

Definition 11.5.1 An n×n matrix A is diagonalizable if there exists an invertible matrix Ssuch that

S−1AS = D

where D is a diagonal matrix.

The following theorem gives the condition under which a matrix is diagonalizable.

Theorem 11.5.2 An n× n matrix S is invertible if and only if its columns are linearlyindependent.