Let
A = [ 1 1 2 1 2 1 2 1 1 ] A=\begin{bmatrix}
1 & 1 & 2 \\
1 & 2 & 1 \\
2 & 1 & 1
\end{bmatrix} A = ⎣ ⎡ 1 1 2 1 2 1 2 1 1 ⎦ ⎤
A − λ I = [ 1 − λ 1 2 1 2 − λ 1 2 1 1 − λ ] A-\lambda I=\begin{bmatrix}
1-\lambda & 1 & 2 \\
1 & 2-\lambda & 1 \\
2 & 1 & 1-\lambda
\end{bmatrix} A − λ I = ⎣ ⎡ 1 − λ 1 2 1 2 − λ 1 2 1 1 − λ ⎦ ⎤
d e t ( A − λ I ) = ∣ 1 − λ 1 2 1 2 − λ 1 2 1 1 − λ ∣ = det(A-\lambda I)=\begin{vmatrix}
1-\lambda & 1 & 2 \\
1 & 2-\lambda & 1 \\
2 & 1 & 1-\lambda
\end{vmatrix}= d e t ( A − λ I ) = ∣ ∣ 1 − λ 1 2 1 2 − λ 1 2 1 1 − λ ∣ ∣ =
= ( 1 − λ ) ∣ 2 − λ 1 1 1 − λ ∣ − ( 1 ) ∣ 1 1 2 1 − λ ∣ + ( 2 ) ∣ 1 2 − λ 2 1 ∣ = = (1-\lambda)\begin{vmatrix}
2-\lambda & 1 \\
1 & 1-\lambda
\end{vmatrix}-(1)\begin{vmatrix}
1 & 1 \\
2 & 1-\lambda
\end{vmatrix}+(2)\begin{vmatrix}
1 & 2-\lambda \\
2 & 1
\end{vmatrix}= = ( 1 − λ ) ∣ ∣ 2 − λ 1 1 1 − λ ∣ ∣ − ( 1 ) ∣ ∣ 1 2 1 1 − λ ∣ ∣ + ( 2 ) ∣ ∣ 1 2 2 − λ 1 ∣ ∣ =
= ( 1 − λ ) ( 2 − 2 λ − λ + λ 2 − 1 ) − ( 1 − λ − 2 ) + =(1-\lambda)(2-2\lambda-\lambda+\lambda^2-1)-(1-\lambda-2)+ = ( 1 − λ ) ( 2 − 2 λ − λ + λ 2 − 1 ) − ( 1 − λ − 2 ) +
+ 2 ( 1 − 4 + 2 λ ) = 1 − 3 λ + λ 2 − λ + 3 λ 2 − λ 3 + 5 λ − 5 = +2(1-4+2\lambda)=1-3\lambda+\lambda^2-\lambda+3\lambda^2-\lambda^3+5\lambda-5= + 2 ( 1 − 4 + 2 λ ) = 1 − 3 λ + λ 2 − λ + 3 λ 2 − λ 3 + 5 λ − 5 =
= − λ 3 + 4 λ 2 + λ − 4 =-\lambda^3+4\lambda^2+\lambda-4 = − λ 3 + 4 λ 2 + λ − 4 This is a characteristic polynomial.
Solve d e t ( A − λ I ) = 0 det(A-\lambda I)=0 d e t ( A − λ I ) = 0
− λ 3 + 4 λ 2 + λ − 4 = 0 -\lambda^3+4\lambda^2+\lambda-4=0 − λ 3 + 4 λ 2 + λ − 4 = 0 − λ 2 ( λ − 4 ) + ( λ − 4 ) = 0 -\lambda^2(\lambda-4)+(\lambda-4)=0 − λ 2 ( λ − 4 ) + ( λ − 4 ) = 0 ( λ − 4 ) ( 1 − λ ) ( 1 + λ ) = 0 (\lambda-4)(1-\lambda)(1+\lambda)=0 ( λ − 4 ) ( 1 − λ ) ( 1 + λ ) = 0 The roots are: λ 1 = 4 , λ 2 = 1 , λ 3 = − 1. \lambda_1=4,\lambda_2=1,\lambda_3=-1. λ 1 = 4 , λ 2 = 1 , λ 3 = − 1.
These are the eigenvalues.
Find the eigenvectors.
λ = 4 \lambda=4 λ = 4
[ 1 − λ 1 2 1 2 − λ 1 2 1 1 − λ ] = [ − 3 1 2 1 − 2 1 2 1 − 3 ] \begin{bmatrix}
1-\lambda & 1 & 2 \\
1 & 2-\lambda & 1 \\
2 & 1 & 1-\lambda
\end{bmatrix}=\begin{bmatrix}
-3 & 1 & 2 \\
1 & -2 & 1 \\
2 & 1 & -3
\end{bmatrix} ⎣ ⎡ 1 − λ 1 2 1 2 − λ 1 2 1 1 − λ ⎦ ⎤ = ⎣ ⎡ − 3 1 2 1 − 2 1 2 1 − 3 ⎦ ⎤ Perform row operations to obtain the rref of the matrix:
R 2 = R 2 + ( 1 / 3 ) R 1 R_2=R_2+(1/3)R_1 R 2 = R 2 + ( 1/3 ) R 1
[ − 3 1 2 0 − 5 / 3 5 / 3 2 1 − 3 ] \begin{bmatrix}
-3 & 1 & 2 \\
0 & -5/3 & 5/3 \\
2 & 1 & -3
\end{bmatrix} ⎣ ⎡ − 3 0 2 1 − 5/3 1 2 5/3 − 3 ⎦ ⎤ R 3 = R 3 + ( 2 / 3 ) R 1 R_3=R_3+(2/3)R_1 R 3 = R 3 + ( 2/3 ) R 1
[ − 3 1 2 0 − 5 / 3 5 / 3 0 5 / 3 − 5 / 3 ] \begin{bmatrix}
-3 & 1 & 2 \\
0 & -5/3 & 5/3 \\
0 & 5/3 & -5/3
\end{bmatrix} ⎣ ⎡ − 3 0 0 1 − 5/3 5/3 2 5/3 − 5/3 ⎦ ⎤ R 3 = R 3 + R 2 R_3=R_3+R_2 R 3 = R 3 + R 2
[ − 3 1 2 0 − 5 / 3 5 / 3 0 0 0 ] \begin{bmatrix}
-3 & 1 & 2 \\
0 & -5/3 & 5/3 \\
0 & 0 & 0
\end{bmatrix} ⎣ ⎡ − 3 0 0 1 − 5/3 0 2 5/3 0 ⎦ ⎤ R 2 = ( − 3 / 5 ) R 2 R_2=(-3/5)R_2 R 2 = ( − 3/5 ) R 2
[ − 3 1 2 0 1 − 1 0 0 0 ] \begin{bmatrix}
-3 & 1 & 2 \\
0 & 1 & -1 \\
0 & 0 & 0
\end{bmatrix} ⎣ ⎡ − 3 0 0 1 1 0 2 − 1 0 ⎦ ⎤ R 1 = R 1 − R 2 R_1=R_1-R_2 R 1 = R 1 − R 2
[ − 3 0 3 0 1 − 1 0 0 0 ] \begin{bmatrix}
-3 & 0 & 3 \\
0 & 1 & -1 \\
0 & 0 & 0
\end{bmatrix} ⎣ ⎡ − 3 0 0 0 1 0 3 − 1 0 ⎦ ⎤ R 1 = ( − 1 / 3 ) R 1 R_1=(-1/3)R_1 R 1 = ( − 1/3 ) R 1
[ 1 0 − 1 0 1 − 1 0 0 0 ] \begin{bmatrix}
1 & 0 & -1 \\
0 & 1 & -1 \\
0 & 0 & 0
\end{bmatrix} ⎣ ⎡ 1 0 0 0 1 0 − 1 − 1 0 ⎦ ⎤ Now, solve the matrix equation
[ 1 0 − 1 0 1 − 1 0 0 0 ] [ v 1 v 2 v 3 ] = [ 0 0 0 ] \begin{bmatrix}
1 & 0 & -1 \\
0 & 1 & -1 \\
0 & 0 & 0
\end{bmatrix}\begin{bmatrix}
v_1 \\
v_2 \\
v_3
\end{bmatrix}=\begin{bmatrix}
0 \\
0 \\
0
\end{bmatrix} ⎣ ⎡ 1 0 0 0 1 0 − 1 − 1 0 ⎦ ⎤ ⎣ ⎡ v 1 v 2 v 3 ⎦ ⎤ = ⎣ ⎡ 0 0 0 ⎦ ⎤ If we take v 3 = t , v_3=t, v 3 = t , then v 1 = t , v 2 = t , v 3 = t . v_1=t, v_2=t,v_3=t. v 1 = t , v 2 = t , v 3 = t .
Therefore
v = [ t t t ] = [ 1 1 1 ] t \mathbf {v}=\begin{bmatrix}
t \\
t \\
t
\end{bmatrix}=\begin{bmatrix}
1 \\
1 \\
1
\end{bmatrix}t v = ⎣ ⎡ t t t ⎦ ⎤ = ⎣ ⎡ 1 1 1 ⎦ ⎤ t λ = 1 \lambda=1 λ = 1
[ 1 − λ 1 2 1 2 − λ 1 2 1 1 − λ ] = [ 0 1 2 1 1 1 2 1 0 ] \begin{bmatrix}
1-\lambda & 1 & 2 \\
1 & 2-\lambda & 1 \\
2 & 1 & 1-\lambda
\end{bmatrix}=\begin{bmatrix}
0 & 1 & 2 \\
1 & 1 & 1 \\
2 & 1 & 0
\end{bmatrix} ⎣ ⎡ 1 − λ 1 2 1 2 − λ 1 2 1 1 − λ ⎦ ⎤ = ⎣ ⎡ 0 1 2 1 1 1 2 1 0 ⎦ ⎤ Perform row operations to obtain the rref of the matrix:
Swap rows 1 and 2
[ 1 1 1 0 1 2 2 1 0 ] \begin{bmatrix}
1 & 1 & 1 \\
0 & 1 & 2 \\
2 & 1 & 0
\end{bmatrix} ⎣ ⎡ 1 0 2 1 1 1 1 2 0 ⎦ ⎤ R 3 = R 3 − ( 2 ) R 1 R_3=R_3-(2)R_1 R 3 = R 3 − ( 2 ) R 1
[ 1 1 1 0 1 2 0 − 1 − 2 ] \begin{bmatrix}
1 & 1 & 1 \\
0 & 1 & 2 \\
0 & -1 & -2
\end{bmatrix} ⎣ ⎡ 1 0 0 1 1 − 1 1 2 − 2 ⎦ ⎤ R 3 = R 3 + R 2 R_3=R_3+R_2 R 3 = R 3 + R 2
[ 1 1 1 0 1 2 0 0 0 ] \begin{bmatrix}
1 & 1 & 1 \\
0 & 1 & 2 \\
0 & 0 & 0
\end{bmatrix} ⎣ ⎡ 1 0 0 1 1 0 1 2 0 ⎦ ⎤ R 1 = R 1 − R 2 R_1=R_1-R_2 R 1 = R 1 − R 2
[ 1 0 − 1 0 1 2 0 0 0 ] \begin{bmatrix}
1 & 0 & -1 \\
0 & 1 & 2 \\
0 & 0 & 0
\end{bmatrix} ⎣ ⎡ 1 0 0 0 1 0 − 1 2 0 ⎦ ⎤ Now, solve the matrix equation
[ 1 0 − 1 0 1 2 0 0 0 ] [ u 1 u 2 u 3 ] = [ 0 0 0 ] \begin{bmatrix}
1 & 0 & -1 \\
0 & 1 & 2 \\
0 & 0 & 0
\end{bmatrix}\begin{bmatrix}
u_1 \\
u_2 \\
u_3
\end{bmatrix}=\begin{bmatrix}
0 \\
0 \\
0
\end{bmatrix} ⎣ ⎡ 1 0 0 0 1 0 − 1 2 0 ⎦ ⎤ ⎣ ⎡ u 1 u 2 u 3 ⎦ ⎤ = ⎣ ⎡ 0 0 0 ⎦ ⎤ If we take u 3 = t , u_3=t, u 3 = t , then u 1 = t , u 2 = − 2 t , u 3 = t . u_1=t, u_2=-2t,u_3=t. u 1 = t , u 2 = − 2 t , u 3 = t .
Therefore
u = [ t − 2 t t ] = [ 1 − 2 1 ] t \mathbf {u}=\begin{bmatrix}
t \\
-2t \\
t
\end{bmatrix}=\begin{bmatrix}
1 \\
-2 \\
1
\end{bmatrix}t u = ⎣ ⎡ t − 2 t t ⎦ ⎤ = ⎣ ⎡ 1 − 2 1 ⎦ ⎤ t λ = − 1 \lambda=-1 λ = − 1
[ 1 − λ 1 2 1 2 − λ 1 2 1 1 − λ ] = [ 2 1 2 1 3 1 2 1 2 ] \begin{bmatrix}
1-\lambda & 1 & 2 \\
1 & 2-\lambda & 1 \\
2 & 1 & 1-\lambda
\end{bmatrix}=\begin{bmatrix}
2 & 1 & 2 \\
1 & 3 & 1 \\
2 & 1 & 2
\end{bmatrix} ⎣ ⎡ 1 − λ 1 2 1 2 − λ 1 2 1 1 − λ ⎦ ⎤ = ⎣ ⎡ 2 1 2 1 3 1 2 1 2 ⎦ ⎤ Perform row operations to obtain the rref of the matrix:
R 3 = R 3 − R 1 R_3=R_3-R_1 R 3 = R 3 − R 1
[ 2 1 2 1 3 1 0 0 0 ] \begin{bmatrix}
2 & 1 & 2 \\
1 & 3 & 1 \\
0 & 0 & 0
\end{bmatrix} ⎣ ⎡ 2 1 0 1 3 0 2 1 0 ⎦ ⎤ R 2 = R 2 − ( 1 / 2 ) R 1 R_2=R_2-(1/2)R_1 R 2 = R 2 − ( 1/2 ) R 1
[ 2 1 2 0 5 / 2 0 0 0 0 ] \begin{bmatrix}
2 & 1 & 2 \\
0 & 5/2 & 0 \\
0 & 0 & 0
\end{bmatrix} ⎣ ⎡ 2 0 0 1 5/2 0 2 0 0 ⎦ ⎤ R 2 = ( 2 / 5 ) R 2 R_2=(2/5)R_2 R 2 = ( 2/5 ) R 2
[ 2 1 2 0 1 0 0 0 0 ] \begin{bmatrix}
2 & 1 & 2 \\
0 & 1 & 0 \\
0 & 0 & 0
\end{bmatrix} ⎣ ⎡ 2 0 0 1 1 0 2 0 0 ⎦ ⎤ R 1 = R 1 − R 2 R_1=R_1-R_2 R 1 = R 1 − R 2
[ 2 0 2 0 1 0 0 0 0 ] \begin{bmatrix}
2 & 0 & 2 \\
0 & 1 & 0 \\
0 & 0 & 0
\end{bmatrix} ⎣ ⎡ 2 0 0 0 1 0 2 0 0 ⎦ ⎤ R 1 = ( 1 / 2 ) R 1 R_1=(1/2)R_1 R 1 = ( 1/2 ) R 1
[ 1 0 1 0 1 0 0 0 0 ] \begin{bmatrix}
1 & 0 & 1 \\
0 & 1 & 0 \\
0 & 0 & 0
\end{bmatrix} ⎣ ⎡ 1 0 0 0 1 0 1 0 0 ⎦ ⎤ Now, solve the matrix equation
[ 1 0 1 0 1 0 0 0 0 ] [ w 1 w 2 w 3 ] = [ 0 0 0 ] \begin{bmatrix}
1 & 0 & 1 \\
0 & 1 & 0 \\
0 & 0 & 0
\end{bmatrix}\begin{bmatrix}
w_1 \\
w_2 \\
w_3
\end{bmatrix}=\begin{bmatrix}
0 \\
0 \\
0
\end{bmatrix} ⎣ ⎡ 1 0 0 0 1 0 1 0 0 ⎦ ⎤ ⎣ ⎡ w 1 w 2 w 3 ⎦ ⎤ = ⎣ ⎡ 0 0 0 ⎦ ⎤ If we take w 3 = t , w_3=t, w 3 = t , then w 1 = − t , w 2 = 0 , w 3 = t . w_1=-t, w_2=0, w_3=t. w 1 = − t , w 2 = 0 , w 3 = t .
Therefore
w = [ − t 0 t ] = [ − 1 0 1 ] t \mathbf {w}=\begin{bmatrix}
-t \\
0 \\
t
\end{bmatrix}=\begin{bmatrix}
-1 \\
0 \\
1
\end{bmatrix}t w = ⎣ ⎡ − t 0 t ⎦ ⎤ = ⎣ ⎡ − 1 0 1 ⎦ ⎤ t Eigen value: 4 , 4, 4 , eigenvector:[ 1 / 3 1 / 3 1 / 3 ] \begin{bmatrix}
1/\sqrt{3} \\
1/\sqrt{3} \\
1/\sqrt{3}
\end{bmatrix} ⎣ ⎡ 1/ 3 1/ 3 1/ 3 ⎦ ⎤
Eigen value: 1 , 1, 1 , eigenvector: [ 1 / 6 − 2 / 6 1 / 6 ] \begin{bmatrix}
1/\sqrt{6} \\
-2/\sqrt{6} \\
1/\sqrt{6}
\end{bmatrix} ⎣ ⎡ 1/ 6 − 2/ 6 1/ 6 ⎦ ⎤
Figenvalue: − 1 , -1, − 1 , eigenvector: [ − 1 / 2 0 1 / 2 ] \begin{bmatrix}
-1/\sqrt{2} \\
0 \\
1/\sqrt{2}
\end{bmatrix} ⎣ ⎡ − 1/ 2 0 1/ 2 ⎦ ⎤
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