Solution;
The matrix representation,A,of the equation is;
A = ( 3 1 1 1 3 − 1 1 − 1 3 ) A=\begin{pmatrix}
3 & 1&1\\
1 & 3&-1\\
1&-1&3
\end{pmatrix} A = ⎝ ⎛ 3 1 1 1 3 − 1 1 − 1 3 ⎠ ⎞
Find the characteristic equation from,
∣ A − λ I ∣ = 0 |A-\lambda I|=0 ∣ A − λ I ∣ = 0
i.e;
λ 3 − s 1 λ 2 + s 2 λ − s 3 = 0 \lambda^3-s_1\lambda^2+s_2\lambda-s_3=0 λ 3 − s 1 λ 2 + s 2 λ − s 3 = 0
In which ;
s 1 s_1 s 1 =Sum of the main diagonal elements.
s 1 = 3 + 3 + 3 = 9 s_1=3+3+3=9 s 1 = 3 + 3 + 3 = 9
s 2 s_2 s 2 = Sum of the minors of the main diagonal elements;
s 2 = ∣ 3 1 1 3 ∣ s_2=\begin{vmatrix}
3 & 1 \\
1& 3
\end{vmatrix} s 2 = ∣ ∣ 3 1 1 3 ∣ ∣ +∣ 3 1 1 3 ∣ \begin{vmatrix}
3 & 1\\
1 & 3
\end{vmatrix} ∣ ∣ 3 1 1 3 ∣ ∣ +∣ 3 − 1 − 1 3 ∣ \begin{vmatrix}
3& -1 \\
-1 & 3
\end{vmatrix} ∣ ∣ 3 − 1 − 1 3 ∣ ∣
s 2 = 24 s_2=24 s 2 = 24
s 3 s_3 s 3 =|A|=∣ 3 1 1 1 3 − 1 1 − 1 3 ∣ \begin{vmatrix}
3& 1&1 \\
1 & 3&-1\\
1&-1&3
\end{vmatrix} ∣ ∣ 3 1 1 1 3 − 1 1 − 1 3 ∣ ∣ =16
The characteristic equation is ;
λ 3 − 9 λ 2 + 24 λ − 16 = 0 \lambda^3-9\lambda^2+24\lambda-16=0 λ 3 − 9 λ 2 + 24 λ − 16 = 0
Solve for the roots of the equation;
If λ = 1 \lambda=1 λ = 1
1-9+24-16=0
Hence ,λ = 1 \lambda =1 λ = 1 is a root.
By synthetic Division,other roots are from;
λ 2 − 8 λ + 16 = 0 \lambda ^2-8\lambda+16=0 λ 2 − 8 λ + 16 = 0
( λ − 4 ) ( λ − 4 ) = 0 (\lambda-4)(\lambda-4)=0 ( λ − 4 ) ( λ − 4 ) = 0
λ = 4 , 4 \lambda=4,4 λ = 4 , 4
Hence the eigenvalues are;
4,4,1
Find the eigenvectors;
(A-λ I \lambda I λ I )x=0
[ ( 3 1 1 1 3 − 1 1 − 1 3 ) [\begin{pmatrix}
3 &1&1\\
1& 3&-1\\
1&-1&3
\end{pmatrix} [ ⎝ ⎛ 3 1 1 1 3 − 1 1 − 1 3 ⎠ ⎞ -( λ 0 0 λ 0 0 0 λ ) ] x = 0 \begin{pmatrix}
\lambda & 0 \\
0 & \lambda&0\\
0&0&\lambda
\end{pmatrix}]x=0 ⎝ ⎛ λ 0 0 0 λ 0 0 λ ⎠ ⎞ ] x = 0
To have;
[ 3 − λ 1 1 1 3 − λ − 1 1 − 1 3 − λ ] \begin{bmatrix}
3-\lambda & 1&1 \\
1 & 3-\lambda&-1\\
1&-1&3-\lambda
\end{bmatrix} ⎣ ⎡ 3 − λ 1 1 1 3 − λ − 1 1 − 1 3 − λ ⎦ ⎤ [ x y z ] = 0 \begin{bmatrix}
x \\
y\\
z\\
\end{bmatrix}=0 ⎣ ⎡ x y z ⎦ ⎤ = 0
Take;
Case (i),if λ \lambda λ =4,the equation becomes;
[ − 1 1 1 1 − 1 − 1 1 − 1 − 1 ] \begin{bmatrix}
-1& 1&1\\
1 & -1&-1\\
1&-1&-1
\end{bmatrix} ⎣ ⎡ − 1 1 1 1 − 1 − 1 1 − 1 − 1 ⎦ ⎤ [ x y z ] = 0 \begin{bmatrix}
x \\
y\\
z\\
\end{bmatrix}=0 ⎣ ⎡ x y z ⎦ ⎤ = 0
-x+y+z=0
x-y-z=0
x-y-z=0
The equation gives ;
x 1 = [ 2 1 1 ] x_1=\begin{bmatrix}
2\\
1\\
1
\end{bmatrix} x 1 = ⎣ ⎡ 2 1 1 ⎦ ⎤
Case(iii),λ = 1 \lambda =1 λ = 1 ,the equation becomes;
[ 2 1 1 1 2 − 1 1 − 1 2 ] \begin{bmatrix}
2 & 1&1\\
1 & 2&-1\\
1&-1&2
\end{bmatrix} ⎣ ⎡ 2 1 1 1 2 − 1 1 − 1 2 ⎦ ⎤ [ x y z ] = 0 \begin{bmatrix}
x\\
y\\
z
\end{bmatrix}=0 ⎣ ⎡ x y z ⎦ ⎤ = 0
2x+y+z=0
x+2y-z=0
x-y+2y=0
The equations give;
x 3 = [ − 1 1 1 ] x_3=\begin{bmatrix}
-1\\
1\\
1
\end{bmatrix} x 3 = ⎣ ⎡ − 1 1 1 ⎦ ⎤
To find the third set of eigenvectors,x 3 x_3 x 3
Since;
x 1 x 2 T = 0 x_1x_2^T=0 x 1 x 2 T = 0
x 2 x 3 T = 0 x_2x_3^T=0 x 2 x 3 T = 0
x 3 x 1 T = 0 x_3x_1^T=0 x 3 x 1 T = 0
We know;
x 1 = [ 2 1 1 ] x_1=\begin{bmatrix}
2 \\
1\\
1
\end{bmatrix} x 1 = ⎣ ⎡ 2 1 1 ⎦ ⎤ ,x 3 = [ − 1 1 1 ] x_3=\begin{bmatrix}
-1\\
1\\
1
\end{bmatrix} x 3 = ⎣ ⎡ − 1 1 1 ⎦ ⎤
Let ;
x 2 = [ a b c ] x_2=\begin{bmatrix}
a \\
b\\
c
\end{bmatrix} x 2 = ⎣ ⎡ a b c ⎦ ⎤
Hence;
[ 2 1 1 − 1 1 1 ] \begin{bmatrix}
2 & 1&1 \\
-1 & 1&1
\end{bmatrix} [ 2 − 1 1 1 1 1 ] [ a b c ] = 0 \begin{bmatrix}
a \\
b\\
c
\end{bmatrix}=0 ⎣ ⎡ a b c ⎦ ⎤ = 0
2a+b+c=0
-a+b+c=0
Hence,
x 2 = [ 0 − 1 1 ] x_2=\begin{bmatrix}
0\\
-1\\
1\\
\end{bmatrix} x 2 = ⎣ ⎡ 0 − 1 1 ⎦ ⎤
The model matrix,M from the eigenvectors is;
( 2 0 − 1 1 − 1 1 1 1 1 ) \begin{pmatrix}
2 & 0&-1\\
1 & -1&1\\
1&1&1
\end{pmatrix} ⎝ ⎛ 2 1 1 0 − 1 1 − 1 1 1 ⎠ ⎞
The normalised model matrix ,N,is as follows;
Length of eigenvectors;
x 1 = 4 + 1 + 1 = 6 x_1=\sqrt{4+1+1}=\sqrt6 x 1 = 4 + 1 + 1 = 6
x 2 = 0 + 1 + 1 = 2 x_2=\sqrt{0+1+1}=\sqrt2 x 2 = 0 + 1 + 1 = 2
x 3 = 1 + 1 + 1 = 3 x_3=\sqrt{1+1+1}=\sqrt 3 x 3 = 1 + 1 + 1 = 3
N = [ 2 6 0 − 1 3 1 6 − 1 2 1 3 1 6 1 2 1 3 ] N=\begin{bmatrix}
\frac{2}{\sqrt6}&0&\frac{-1}{\sqrt3} \\
\frac{1}{\sqrt6} & \frac{-1}{\sqrt2}&\frac{1}{\sqrt3}\\
\frac{1}{\sqrt6}&\frac{1}{\sqrt2}&\frac{1}{\sqrt3}
\end{bmatrix} N = ⎣ ⎡ 6 2 6 1 6 1 0 2 − 1 2 1 3 − 1 3 1 3 1 ⎦ ⎤
Transponse normalised model matrix ,N T N^T N T ;
N T = [ 2 6 1 6 1 6 0 − 1 2 1 2 − 1 3 1 3 1 3 ] N^T=\begin{bmatrix}
\frac{2}{\sqrt6}&\frac{1}{\sqrt6}&\frac{1}{\sqrt6} \\
0 & \frac{-1}{\sqrt2}&\frac{1}{\sqrt2}\\
\frac{-1}{\sqrt3}&\frac{1}{\sqrt3}&\frac{1}{\sqrt3}
\end{bmatrix} N T = ⎣ ⎡ 6 2 0 3 − 1 6 1 2 − 1 3 1 6 1 2 1 3 1 ⎦ ⎤
Find the diagonalized matrix,D = N T A N D=N^TAN D = N T A N
D = [ 4 0 0 0 4 0 0 0 1 ] D=\begin{bmatrix}
4 & 0&0 \\
0 & 4&0\\
0&0&1
\end{bmatrix} D = ⎣ ⎡ 4 0 0 0 4 0 0 0 1 ⎦ ⎤
Hence D is the matrix of linear transformation of the quadratic form into canonical form.
Thus the linear transformation,X is;
X=Dy
X=( 4 0 0 0 4 0 0 0 1 ) \begin{pmatrix}
4& 0&0 \\
0 & 4&0\\
0&0&1
\end{pmatrix} ⎝ ⎛ 4 0 0 0 4 0 0 0 1 ⎠ ⎞ ( y 1 , y 2 , y 3 ) (y_1,y_2,y_3) ( y 1 , y 2 , y 3 )
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