Matrix A= ( 2 0 0 0 2 1 0 1 2 ) =\begin{pmatrix}
2&0&0 \\
0&2&1 \\
0&1&2
\end{pmatrix} = ⎝ ⎛ 2 0 0 0 2 1 0 1 2 ⎠ ⎞
∣ A − λ I ∣ = ∣ 2 − λ 0 0 0 2 − λ 1 0 1 2 − λ ∣ = 0 \>\>\begin{vmatrix}
A-\lambda\>I \\
\end{vmatrix}=\begin{vmatrix}
2-\lambda&0&0 \\
0&2-\lambda& 1\\
0&1&2-\lambda
\end{vmatrix}=0 ∣ ∣ A − λ I ∣ ∣ = ∣ ∣ 2 − λ 0 0 0 2 − λ 1 0 1 2 − λ ∣ ∣ = 0
( 2 − λ ) [ ( 2 − λ ) ( 2 − λ ) − 1 ] + 0 + 0 = 0 (2-\lambda)\begin{bmatrix}
(2-\lambda)(2-\lambda)-1\\
\end{bmatrix}+0+0=0 ( 2 − λ ) [ ( 2 − λ ) ( 2 − λ ) − 1 ] + 0 + 0 = 0
( 2 − λ ) ( λ 2 − 4 λ + 3 ) = 0 (2-\lambda)(\lambda^2-4\lambda+3)=0 ( 2 − λ ) ( λ 2 − 4 λ + 3 ) = 0
( 2 − λ ) ( λ − 1 ) ( λ − 3 ) = 0 (2-\lambda)(\lambda-1)(\lambda-3)=0 ( 2 − λ ) ( λ − 1 ) ( λ − 3 ) = 0
λ = 1 , λ = 2 , λ = 3 \lambda=1,\lambda=2,\lambda=3 λ = 1 , λ = 2 , λ = 3
For λ = 1 , ( 1 0 0 0 1 1 0 1 1 ) ( x 1 x 2 x 3 ) = ( 0 0 0 ) \lambda=1,\begin{pmatrix}
1&0&0 \\
0&1&1 \\
0&1&1
\end{pmatrix}\begin{pmatrix}
x_1 \\
x_2 \\
x_3
\end{pmatrix}=\begin{pmatrix}
0 \\
0\\
0
\end{pmatrix} λ = 1 , ⎝ ⎛ 1 0 0 0 1 1 0 1 1 ⎠ ⎞ ⎝ ⎛ x 1 x 2 x 3 ⎠ ⎞ = ⎝ ⎛ 0 0 0 ⎠ ⎞
x 1 = 0 , x 2 = − 1 , x 3 = 1 x_1=0,\>x_2=-1,\>x_3=1 x 1 = 0 , x 2 = − 1 , x 3 = 1
For λ = 2 ( 0 0 0 0 0 1 0 1 0 ) ( x 1 x 2 x 3 ) = ( 0 0 0 ) \lambda=2\begin{pmatrix}
0&0 & 0 \\
0&0 & 1\\
0&1&0
\end{pmatrix}\begin{pmatrix}
x_1 \\
x_2 \\
x_3
\end{pmatrix}=\begin{pmatrix}
0 \\
0 \\
0
\end{pmatrix} λ = 2 ⎝ ⎛ 0 0 0 0 0 1 0 1 0 ⎠ ⎞ ⎝ ⎛ x 1 x 2 x 3 ⎠ ⎞ = ⎝ ⎛ 0 0 0 ⎠ ⎞
x 1 = 1 , x 2 = 0 , x 3 = 0 x_1=1,\>x_2=0,\>x_3=0 x 1 = 1 , x 2 = 0 , x 3 = 0
For λ = 3 ( − 1 0 0 0 − 1 1 0 1 − 1 ) ( x 1 x 2 x 3 ) = ( 0 0 0 ) \lambda=3\begin{pmatrix}
-1&0&0 \\
0&-1 & 1\\
0&1&-1
\end{pmatrix}\begin{pmatrix}
x_1 \\
x_2\\
x_3
\end{pmatrix}=\begin{pmatrix}
0 \\
0\\
0
\end{pmatrix} λ = 3 ⎝ ⎛ − 1 0 0 0 − 1 1 0 1 − 1 ⎠ ⎞ ⎝ ⎛ x 1 x 2 x 3 ⎠ ⎞ = ⎝ ⎛ 0 0 0 ⎠ ⎞
x 1 = 0 , x 2 = 1 , x 3 = 1 x_1=0,\>x_2=1,\>x_3=1 x 1 = 0 , x 2 = 1 , x 3 = 1
Modal matrix ( 0 1 0 − 1 0 1 1 0 1 ) \begin{pmatrix}
0&1&0 \\
-1&0&1\\
1&0&1
\end{pmatrix} ⎝ ⎛ 0 − 1 1 1 0 0 0 1 1 ⎠ ⎞
Normalized modal matrix
Q = ( 0 1 0 − 1 2 0 1 2 1 2 0 1 2 ) Q=\begin{pmatrix}
0&1&0 \\
\frac{-1}{\sqrt2} & 0&\frac{1}{\sqrt2}\\
\frac{1}{\sqrt2}&0&\frac{1}{\sqrt2}
\end{pmatrix} Q = ⎝ ⎛ 0 2 − 1 2 1 1 0 0 0 2 1 2 1 ⎠ ⎞
Diagonalizing matrix
D = Q T A Q = ( 0 − 1 2 1 2 1 0 0 0 1 2 1 2 ) ( 2 0 0 0 2 1 0 1 2 ) ( 0 1 0 − 1 2 0 1 2 1 2 0 1 2 ) D=Q^TAQ=\begin{pmatrix}
0&\frac{-1}{\sqrt2}& \frac{1}{\sqrt2} \\
1&0&0 \\
0&\frac{1}{\sqrt2}&\frac{1}{\sqrt2}
\end{pmatrix}\begin{pmatrix}
2&0&0 \\
0&2 & 1\\
0&1&2
\end{pmatrix}\begin{pmatrix}
0&1&0 \\
\frac{-1}{\sqrt2}&0&\frac{1}{\sqrt2} \\
\frac{1}{\sqrt2}&0&\frac{1}{\sqrt2}
\end{pmatrix} D = Q T A Q = ⎝ ⎛ 0 1 0 2 − 1 0 2 1 2 1 0 2 1 ⎠ ⎞ ⎝ ⎛ 2 0 0 0 2 1 0 1 2 ⎠ ⎞ ⎝ ⎛ 0 2 − 1 2 1 1 0 0 0 2 1 2 1 ⎠ ⎞
= ( 1 0 0 0 2 0 0 0 3 ) =\begin{pmatrix}
1&0&0 \\
0&2& 0\\
0&0&3
\end{pmatrix} = ⎝ ⎛ 1 0 0 0 2 0 0 0 3 ⎠ ⎞
Diagonalized matrix has principal diagonal element =Eigenvalues
All other elements= 0 =0 = 0
The orthogonal transformation reduces the quadratic form to conical form
y 1 2 + 2 y 2 2 + 3 y 3 2 y_1^2+2y_2^2+3y_3^2 y 1 2 + 2 y 2 2 + 3 y 3 2
Index= 3 =3 = 3
Signature= 2 × 3 − 3 = 3 =2×3-3=3 = 2 × 3 − 3 = 3
Nature of quadratic form
Positive definate
Comments