Is There a Faster Way to Find the Reduced Row Echelon Form of a Matrix?

In summary, the conversation discusses finding the elimination matrices in order to obtain the reduced row-echelon form of a matrix. The interlocutors also consider different methods for obtaining the composite E's and the final matrix G. One suggests using the identity matrix and row reduction, while another mentions using MATLAB as the quickest method.
  • #1
rocomath
1,755
1
So I found the elimination matrices such that [tex]G_3G_2G_1A=rref(A)[/tex] which, but it took way too long. Is there a shorter method?
 
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  • #2
I don't understand what were you trying to find. You want to find the matrix E such that EA = reduced row-echelon form of A ?

If so, I don't see any easy way to get it. Note that the elementary matrix corresponding to a row operation is simply the identity matrix with that same row operation performed on it. Just keep a simple record of all the types of row reduction you did, then you can easily get E from them.
 
  • #3
Just thought about this a little longer and realized that if all you want is the final matrix G which is a matrix product of all the E's, then one way you could get it would be to juxtapose the identity matrix next to A and and row reduce A to it's reduced row echelon form. The resultant matrix next to rref(A) would be G. If you want the composite E's you'll have to solve as above.
 
  • #4
That's what my classmate told me as well, I haven't verified that method yet.

I did what you said in the first post, took me forever to get G through all the E's, LOL.
 
  • #5
Lol much quicker! :)))
 
  • #6
Well the quickest way of course would be to use MATLAB. But that's cheating.
 

What is Linear Algebra?

Linear algebra is a branch of mathematics that deals with linear equations and their representations in vector spaces. It involves the study of linear transformations, matrices, and systems of linear equations.

What is GA=rref(A)?

GA=rref(A) stands for Gauss-Jordan elimination of the matrix A. It is a method used to find the reduced row echelon form (rref) of a matrix, which is the most simplified and useful form of a matrix.

What is the importance of Linear Algebra in science?

Linear algebra is essential in many scientific fields, including physics, engineering, computer science, and data analysis. It provides a powerful tool for representing and solving complex systems of equations, making it a fundamental tool in scientific research and problem-solving.

What are the applications of GA=rref(A)?

GA=rref(A) has various applications, such as solving systems of linear equations, determining the linear independence of vectors, finding the inverse of a matrix, and solving optimization problems. It is also used in computer graphics, machine learning, and statistics.

What are some real-world examples of Linear Algebra and GA=rref(A)?

Linear algebra and GA=rref(A) are used in many real-world applications, such as image and signal processing, cryptography, and circuit design. They are also used in financial modeling, population dynamics, and game theory. Additionally, GA=rref(A) is used in solving systems of equations in physics, chemistry, and biology.

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