Proving the Relationship Between Augmented Matrices and Reduced Row Echelon Form

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SUMMARY

The discussion focuses on proving the relationship between augmented matrices and their reduced row echelon form (RREF). It establishes that if an augmented matrix [A b] has an RREF of [R c], then R is indeed the RREF of A. The definition of RREF is clarified, highlighting that it is achieved through elementary row operations such as row interchange, scaling, and row addition. Key properties of RREF are outlined, including the arrangement of nonzero rows, leading entries, and the requirement for leading entries to be 1.

PREREQUISITES
  • Understanding of linear algebra concepts, specifically augmented matrices.
  • Familiarity with Gaussian elimination techniques.
  • Knowledge of elementary row operations (interchange, scaling, row addition).
  • Comprehension of the definition and properties of reduced row echelon form (RREF).
NEXT STEPS
  • Study the process of Gaussian elimination in detail.
  • Learn how to perform elementary row operations on matrices.
  • Explore examples of converting matrices to reduced row echelon form (RREF).
  • Investigate applications of RREF in solving linear systems.
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Students and educators in linear algebra, mathematicians, and anyone interested in understanding matrix theory and its applications in solving systems of equations.

BK201
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Hi,

i have just started with learning linear algebra ,so please bear with me. It seems like a quite simple question:

Let [A b] an augmented matrix. Prove that if its reduced row echelon form (rref) is [R c] ,then R is the rref of A.
 
Last edited:
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What is the definition of "reduce row echelon form"?
 
First ,thanks for replying.

rref is the simplest and most suitable form for Gaussian Elimination obtained by applying elementary row operations.(interchange ,scaling ,or row addition)

Following are requirements :
1.Every nonzero row lies above each zero row.
2.The leading entry of a nonzero row lies in a column to the right of the column containing the leading entry of any preceding row.
3.If a column contains the leading entry of some row ,then all the other entries in that column are zero.
4.The leading entry of each nonzero row is 1.

ex:

1 0 * * 0 0 *
0 1 * * 0 0 *
0 0 0 0 1 0 *
0 0 0 0 0 1 *
0 0 0 0 0 0 0 (* represents arbitrary real number)

A row with no other entry except zero is referred to zero row ,vice versa.
 
Last edited:

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