How Do I Calculate the Inverse of Matrix P and Determine Eigenvectors?

In summary, the conversation discusses finding the inverse of a matrix and using determinants to simplify the process. It also touches on finding eigenvectors and suggests working them out by hand for better understanding.
  • #1
matrix_204
101
0
Could someone tell me how to get the P(inverse), P^-1. For example I read all the examples in my book and it has like given the matrix for P and then it finds the matrix for P(inverse)Vo , how do i find P^-1. Plz help me quickly.
Ex. P= | 2 -1 |
asdfasf| 3 as1 |
and Vo=| 1 |
iiiiiiiiiiiiiiiiii| 1 |

so P^-1Vo=1/5 [ 2 -1](transpose)
 
Last edited:
Physics news on Phys.org
  • #2
For two by two matrices, it is easy.

For a 2x2 matrix

[tex] A = \left(\begin{array}{cc}a&b\\c&d\end{array}\right) [/tex]

The inverse is just...

[tex] A^{-1} = \frac{1}{\|A\|} \left(\begin{array}{cc}d&-b\\-c&a\end{array}\right)
[/tex]
 
  • #3
thank you very much, it saved me so much time, also, is there a formula for a 3x3 matrix too or no.

btw is ||A||= a^2 + b^2 - c^2 - d^2,
just wondering, i don't know if that's right but what would it be for a 2x2 matrix.
 
Last edited:
  • #5
ok got it, thanx
 
  • #6
And no, what I had

[tex] \|A\| [/tex] is the determinant of A. For a 2x2 matrix

[tex] A = \left(\begin{array}{cc}a&b\\c&d\end{array}\right) [/tex]

[tex] \|A\| = ad - bc [/tex]
 
  • #7
I have one more question, because sometimes its hard to figure out the eigenvector, i was wondering is there a easier way to figure what what the eigenvectors are besides using the equation
http://mathworld.wolfram.com/eimg422.gif
 
Last edited by a moderator:
  • #8
I don't recall so. But please, do yourself a favor and don't work them out by hand. It's just too much boring arithmetic...
 
  • #9
matrix_204 said:
I have one more question, because sometimes its hard to figure out the eigenvector, i was wondering is there a easier way to figure what what the eigenvectors are besides using the equation
http://mathworld.wolfram.com/eimg422.gif

Just to clarify terminology, that equation you linked to gives the eigenvalues, which you then use to find the eigenvectors by looking at the nullspace of [tex]A-\lambda I[/tex], where [tex]\lambda[/tex] is an eigenvalue.

I do suggest you work these out by hand when first learning them. You're more likely to understand what an eigenvector is if you're swimming through the arithmetic trenches than if you're simply entering a matrix into a computer or calculator and having it spit out some answers for you. Of course if you feel you have fully mastered the concept, by all means use mechanical aid (and certainly don't shy from using it to check your work). Just my opinion.
 
Last edited by a moderator:

FAQ: How Do I Calculate the Inverse of Matrix P and Determine Eigenvectors?

What is diagonalization?

Diagonalization is a process of transforming a matrix into a diagonal matrix by finding a set of eigenvectors and eigenvalues that can be used to decompose the original matrix.

Why is diagonalization important?

Diagonalization is important because it simplifies the calculation of matrix operations and makes it easier to solve systems of equations. It also allows for the identification of important patterns and relationships in the data represented by the matrix.

How do I diagonalize a matrix?

To diagonalize a matrix, you need to follow a series of steps including finding the eigenvalues and eigenvectors of the matrix, constructing a diagonal matrix using the eigenvalues, and using the eigenvectors to transform the original matrix into the diagonal matrix.

What are the applications of diagonalization?

Diagonalization has various applications in fields such as physics, engineering, and computer science. It can be used to solve differential equations, analyze dynamical systems, and perform data compression and dimensionality reduction.

Are there any limitations to diagonalization?

Yes, there are limitations to diagonalization. Not all matrices can be diagonalized, and even for those that can, the process may be complex and time-consuming. Additionally, diagonalization does not always provide the most efficient solution for a given problem, and other methods may be more suitable.

Back
Top