Respuesta :
For a given matrix [tex]\mathbf A[/tex] with eigenvalues [tex]\lambda[/tex] and eigenvectors [tex]\mathbf v[/tex], the following relation holds (by definition):
[tex]\mathbf{Av}=\lambda\mathbf v[/tex]
In other words, if [tex]\mathbf v[/tex] is an eigenvector, then the multiplication of [tex]\mathbf v[/tex] by [tex]\mathbf A[/tex] results in a scaled version of the vector [tex]\mathbf v[/tex].
Given the matrix
[tex]\mathbf A=\begin{bmatrix}-1&2\\0&3\end{bmatrix}[/tex]
we want to decide which of the vectors [tex]\mathbf x_i[/tex] are eigenvectors. Taking [tex]\mathbf x_1[/tex], we have
[tex]\mathbf{Ax}_1=\begin{bmatrix}-1&2\\0&3\end{bmatrix}\begin{bmatrix}0\\2\end{bmatrix}=\begin{bmatrix}4\\6\end{bmatrix}[/tex]
but there is no scalar we can remove from the resulting vector to make it a scalar multiple of [tex]\mathbf x_1[/tex]. So [tex]\mathbf x_1[/tex] is not an eigenvector of [tex]\mathbf A[/tex]. We do the same sort of check for the remaining two vectors.
[tex]\mathbf{Ax}_2=\begin{bmatrix}-1&2\\0&3\end{bmatrix}\begin{bmatrix}1\\5\end{bmatrix}=\begin{bmatrix}9\\15\end{bmatrix}[/tex]
Same as before; [tex]\mathbf x_2[/tex] is not an eigenvector of [tex]\mathbf A[/tex].
[tex]\mathbf{Ax}_3=\begin{bmatrix}-1&2\\0&3\end{bmatrix}\begin{bmatrix}1\\2\end{bmatrix}=\begin{bmatrix}3\\6\end{bmatrix}=3\begin{bmatrix}1\\2\end{bmatrix}[/tex]
So [tex]\mathbf x_3[/tex] is an eigenvector of [tex]\mathbf A[/tex] with associated eigenvalue [tex]\lambda=3[/tex].
[tex]\mathbf{Av}=\lambda\mathbf v[/tex]
In other words, if [tex]\mathbf v[/tex] is an eigenvector, then the multiplication of [tex]\mathbf v[/tex] by [tex]\mathbf A[/tex] results in a scaled version of the vector [tex]\mathbf v[/tex].
Given the matrix
[tex]\mathbf A=\begin{bmatrix}-1&2\\0&3\end{bmatrix}[/tex]
we want to decide which of the vectors [tex]\mathbf x_i[/tex] are eigenvectors. Taking [tex]\mathbf x_1[/tex], we have
[tex]\mathbf{Ax}_1=\begin{bmatrix}-1&2\\0&3\end{bmatrix}\begin{bmatrix}0\\2\end{bmatrix}=\begin{bmatrix}4\\6\end{bmatrix}[/tex]
but there is no scalar we can remove from the resulting vector to make it a scalar multiple of [tex]\mathbf x_1[/tex]. So [tex]\mathbf x_1[/tex] is not an eigenvector of [tex]\mathbf A[/tex]. We do the same sort of check for the remaining two vectors.
[tex]\mathbf{Ax}_2=\begin{bmatrix}-1&2\\0&3\end{bmatrix}\begin{bmatrix}1\\5\end{bmatrix}=\begin{bmatrix}9\\15\end{bmatrix}[/tex]
Same as before; [tex]\mathbf x_2[/tex] is not an eigenvector of [tex]\mathbf A[/tex].
[tex]\mathbf{Ax}_3=\begin{bmatrix}-1&2\\0&3\end{bmatrix}\begin{bmatrix}1\\2\end{bmatrix}=\begin{bmatrix}3\\6\end{bmatrix}=3\begin{bmatrix}1\\2\end{bmatrix}[/tex]
So [tex]\mathbf x_3[/tex] is an eigenvector of [tex]\mathbf A[/tex] with associated eigenvalue [tex]\lambda=3[/tex].