Matrix Inversion for Variation of Parameters

In summary, the conversation is about finding the inverse of the Phi matrix using Cramer's Rule. The inverse is set up by breaking the identity matrix into two columns and using Cramer's Rule twice to solve for the a values. The adjoint matrix is also mentioned as a necessary step in finding the inverse. There is some confusion about using 1/Phi(t) as the inverse instead of the correct method of finding the adjoint of Phi and multiplying it by 1/det(Phi).
  • #1
gkirkland
11
0
I am working on the following problem:

DE_zps79b1f9e4.jpg


Can someone please show or explain the steps to invert the phi matrix? I've given it a few tries, but I can't reach what the book has for the answer.

Please help! Thanks
 
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  • #2
Phi(t)*Phi^-1(t) = I, where I is the 2x2 identity matrix.
You can use Cramer's rule to solve for the inverse by breaking the identity matrix into two columns.

If you post some of your work, we may help you spot what is going wrong with you calculations.
 
  • #3
I didn't even think about using Cramer's rule to find the inverse! That was a great idea, got it on the first try.

Thanks!
 
  • #4
So I calculated the inverted matrix, but for some reason I'm still not getting the correct solution. Can someone please spot my mistake?

DifferentialEquationsNotes_Page_2_zps1c63e27a.jpg

DifferentialEquationsNotes_Page_3_zpsbde458ee.jpg
 
  • #5
I apologize for my lack of clarity in my earlier post.

In order to find the inverse of the Phi(t) matrix using Cramer's Rule, it must be used twice.

Code:
This is how the inverse is set up:
| e^-t    e^-2t|  |a11  a12|     |1  0|
|-e^-t  -2e^-2t|  |a21  a22|  =  |0  1|

where the a values represent the inverse of Phi(t). In order to calculate the a values,
the matrix equation above is split into two parts, like so:
Code:
This is how the inverse calculations are set up:
| e^-t   e^-2t|  |a11|     |1|
|-e^-t -2e^-2t|  |a21|  =  |0|
and
| e^-t   e^-2t|  |a12|     |0|
|-e^-t -2e^-2t|  |a22|  =  |1|

Cramer's Rule can be used to solve both systems. Remember, always check the calculations by multiplying Phi(t) by Phi^-1(t) to see if the Identity matrix is obtained.

I should point out that Phi^-1(t) is the inverse matrix of Phi(t) rather than 1/Phi(t)
 
  • #6
isn't the inverse of the matrix 1/det(phi) * adj(phi) not just phi?
You have to find the adjoint of phi then multiply by 1/det(phi), the adjoint matrix being the transpose of the C expansion matrix, for a 2x2 it always works out to be that you swap the signs on entry 2 and 3 and swap the placement of entry 1 and 4.

but I am not sure, trying to work it out now also not getting the books answer..
 

1. What is matrix inversion for variation of parameters?

Matrix inversion for variation of parameters is a mathematical method used to solve systems of differential equations. It involves using the inverse of a matrix to find a particular solution to a system of equations, which can then be combined with the general solution to obtain the complete solution.

2. When is matrix inversion for variation of parameters used?

This method is typically used when the coefficients of a system of differential equations are not constant. It allows for the calculation of a particular solution without requiring the use of series or power series solutions.

3. How does matrix inversion for variation of parameters work?

The method involves finding the inverse of a matrix containing the coefficients of the system of equations. This inverse matrix is then multiplied by a vector containing the known initial conditions, resulting in a vector of constants. These constants can then be used to calculate a particular solution to the system of equations.

4. What are the advantages of using matrix inversion for variation of parameters?

One advantage is that it allows for the calculation of a particular solution without the need for series or power series solutions, which can be tedious and time-consuming. Additionally, this method can be applied to systems of any size, making it a versatile tool for solving differential equations.

5. Are there any limitations to using matrix inversion for variation of parameters?

One limitation is that the method can only be used for systems of linear differential equations. Additionally, it may not always be the most efficient method for solving a particular system, so it is important to consider other techniques as well.

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