Eigenvector Help: Solving Problems 3 & 4

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In summary, the conversation discusses finding eigenvectors and eigenvalues using the matrix A-3E=0, where A is a given matrix and E is the identity matrix. In example 3, the equation e1+e2=0 is obtained by substituting the explicit vector (e1, e2) into (A-3E)e=0. In example 4, the equation e1+2e2+e3=0 is obtained in a similar manner, and the eigenvector (1,-1) is found to correspond to eigenvalue -3. The conversation also mentions the definition of eigenvalues and how they can result in non-unique solutions for the equations.
  • #1
Quadruple Bypass
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http://orion.math.iastate.edu/vika/cal3_files/lec33267.pdf

i searched eigenvectors on google and this showed up. here are some problems i need further explaining for example 3 and 4.

3. where do they get e1+e2= 0 equation from? then where did they get e= (1,-1)

4. where do they get the e1+2e2+e3= 0 eq from?

any help would really be appreciated...i understand how to get the eigenvalues but i have no clue what to do to get the vectors
 
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  • #2
3.
Write out the vector [tex] \vec{e} [/tex] explicitly, i.e. [tex] (e_1,e_2) [/tex], then substitude into [tex] (A-3E) \vec{e} = 0 [/tex], you will see the result immediately.

4.
Same as above...
 
  • #3
The first matrix is
[tex]\left(\begin{array}{cc}-2 & 1 \\ -1 & 4\end{array}\right)[/tex]
which, by solving the "characteristic equation" is determined to have the single eigenvalue -3.

The definition of "eigenvalue" is that there exist a non-trivial (i.e. non-zero) vector v such that [itex]Ax= \lambda x[/itex]. Saying that -3 is an eigenvalue means that there is a non-zero vector
[tex]v= \left(\begin{array}{c}x \\ y\end{array}\right)[/tex]
such that
[tex]\left(\begin{array}{cc}-2 & 1 \\ -1 & 4\end{array}\right)\left(\begin{array}{c}x \\ y\end{array}\right)= \left(\begin{array}{c}-2x+ y \\ -x+ 4y\end{array}\right)= \left(\begin{array}{c}-3x \\ -3y\end{array}\right)[/tex].

The top row says -2x+ y= -3x and the second -x+ 4y= -3y. Normally, two equations in two variables would have a unique solution (and obviously x=0, y= 0 is a solution) but here the equations are not "independent" (precisely because -3 is an eigenvalue). It's easy to see that both equations reduce to y= -x. That is the same as x+y= 0 (your book uses e1+e2= 0 but it is the same thing). Any vector of the form (a, -a)= a(1,-1) is an eigenvector corresponding to eigenvalue -3.
 
  • #4
thanks for the help, hopefully it will make sense with time
 

What are eigenvectors and why are they important?

Eigenvectors are special vectors that do not change direction when multiplied by a specific matrix. They are important because they help us understand the behavior and transformations of a matrix. Eigenvectors also have many applications in fields such as physics, engineering, and computer science.

How do I find the eigenvectors of a matrix?

To find the eigenvectors of a matrix, you first need to calculate the eigenvalues of the matrix. Then, for each eigenvalue, you can solve for its corresponding eigenvector by solving a system of linear equations. The eigenvectors will be the solutions to this system of equations.

What is the difference between an eigenvector and a normal vector?

An eigenvector is a vector that does not change its direction when multiplied by a specific matrix, while a normal vector is perpendicular to a surface or plane. Eigenvectors also have a corresponding eigenvalue, while normal vectors do not.

Can eigenvectors be complex numbers?

Yes, eigenvectors can be complex numbers. This is because the eigenvalues and eigenvectors of a matrix can be complex numbers if the matrix itself has complex numbers as its elements.

How can I use eigenvectors to solve real-world problems?

Eigenvectors have many applications in science and engineering. For example, they can be used to find the principal components of a dataset, which can help us understand the most important features of the data. Eigenvectors can also be used in image and signal processing, as well as in finding the stable states of a physical system.

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