Matrices, Eigenvalues and such...

In summary: Great job on summarizing the content and providing a clear and concise summary of the steps involved in solving this system. Keep up the good work!
  • #1
shamieh
539
0
Consider the system

$x'_1 = -5x_1 + 1x_2$
$x'_2 = 4x_1 - 2x_2$

If we write in matrix form as $X' = AX$ then

a) X =

b) X' =

c) A =

d) Find the eigenvalues of A.

e) Find eigenvectors associated with each eigenvalue. Indicate which eigenvector goes with which eigenvalue.

f) Write the general solution to the system.

g) Find the specific solution that satisfies the initial conditions $x_1(0) = 1$ and $x_2(0) = -2$

So I am not really sure on how to solve these...Here is what I have so far
My Solutions

a) X= $\overrightarrow{X} = (^{x_1} _{x_2})$

b) X' = $(^{-5x_1 + 1x_2}_{4x_1 - 2x_2})$

c) A = $(^{-5}_4$ $^1_{-2})$

d) eig values of A : $\lambda_1 = -1$ and $\lambda_2 = -6$

e) help
f) help
g) refer to e and f (help).
 
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  • #2
I agree with your eigenvalues. To find the eigenvectors, you need to solve the system $(A-\lambda I)x_{\lambda}=0$ for $x_{\lambda}$, which is your eigenvector. You should do this separately, once for each eigenvalue. Each system should be degenerate. What do you get?
 
  • #3
e) so for the eigenvectors i got: \begin{bmatrix} 1 \\ 4 \end{bmatrix} and \begin{bmatrix} 1 \\ -1 \end{bmatrix}

for part f) $X(t) = C_1 \begin{bmatrix} 1 \\ 4 \end{bmatrix}e^{-t} + C_2 \begin{bmatrix} 1 \\ -1 \end{bmatrix}e^{-6t}$

and for part g) I got : $X(t) = -1/5\begin{bmatrix} 1 \\ 4 \end{bmatrix}e^{-t} + 6/5 \begin{bmatrix} 1 \\ -1 \end{bmatrix}e^{-6t}$
 
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  • #4
I'd say you've nailed it!
 

FAQ: Matrices, Eigenvalues and such...

What is a matrix?

A matrix is a rectangular array of numbers, symbols, or expressions arranged in rows and columns. It is used to represent and manipulate data in various mathematical and scientific fields.

What are eigenvalues and eigenvectors?

Eigenvalues and eigenvectors are concepts in linear algebra that are used to understand the behavior of linear transformations on vector spaces. Eigenvalues are the scalar values that represent how a transformation affects the scale of a vector, while eigenvectors are the corresponding vectors that are only scaled by the transformation.

How are eigenvalues and eigenvectors calculated?

Eigenvalues and eigenvectors can be calculated by solving the characteristic equation of a square matrix. The characteristic equation is obtained by subtracting the identity matrix multiplied by a scalar from the original matrix and setting the determinant of the resulting matrix equal to zero.

What is the importance of eigenvalues and eigenvectors?

Eigenvalues and eigenvectors are important in various fields, including physics, engineering, and data analysis. They are used to understand the behavior of complex systems, such as quantum mechanical systems and electrical circuits. In data analysis, they are used to reduce the dimensionality of large datasets and identify patterns in the data.

Can matrices have complex eigenvalues?

Yes, matrices can have complex eigenvalues. In fact, complex eigenvalues often arise in systems that have periodic behavior, such as oscillating systems. Complex eigenvalues can also be used to represent rotations and reflections in geometric transformations.

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