How to Find Inverse of a Matrix

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SUMMARY

This discussion focuses on methods for finding the inverse of a matrix, particularly emphasizing row reduction as the simplest technique. The participant mentions that while row reduction is effective, alternatives such as using the transpose of the matrix of cofactors divided by the determinant are also valid, albeit more complex. The conversation highlights that finding an inverse can be labor-intensive, and often estimations or alternative methods like Gaussian elimination followed by back substitution are preferred. Resources such as Hofstra University's tutorial and Wikipedia's matrix inverse page are referenced for further exploration.

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  • Understanding of matrix operations
  • Familiarity with row reduction techniques
  • Knowledge of determinants and cofactors
  • Basic programming skills in Excel for matrix calculations
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Students in calculus or linear algebra, educators teaching matrix theory, and anyone seeking efficient methods for calculating matrix inverses.

nanoWatt
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Hi,

I'm taking a Calculus I class, so they won't be going into Matrices very much. That's more for Linear Algebra.

I'm going through an E&M book now (as a refresher from my Physics days of 7 years ago). This book assumes knowledge in getting the inverse of a matrix.

Using this site, I was able to find the inverse, by using row reduction. However, I was wondering if there is a quicker or easier way to find a matrix inverse.

http://people.hofstra.edu/Stefan_waner/RealWorld/tutorialsf1/frames3_3.html
 
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Be aware that finding the inverse can be a very long and laborious task. In fact, much of the time this is simply not done, and the inverse is either estimated, which can be done fairly easily to a reasonable degree of accuracy, or else ways around getting the inverse are used, e.g. gauss elimination followed by back substitution.
 
There are a number of different ways of finding an inverse matrix. In my opinion, "row reduction" is the simplest.
 
Another way is to use the fact that the inverse of A is the transpose of the matrix of cofactors of A divided by the determinant of A. Probably more calculations than row reduction, but I find it easier to remember. And for a given size matrix, it's pretty easy to program in Excel.
 

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