Determine the solution set of the system using the echelon form

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SUMMARY

The discussion focuses on determining the solution set of the system using the echelon form of a matrix. The matrix $\displaystyle{a:=\begin{pmatrix}2 & 1 & 0 & 5 \\ 1 & 0 & 1 & 1 \\ 4 & 1 &2 & 7\end{pmatrix}}$ is row reduced using the Gauss algorithm to obtain its echelon form. Participants confirm that the echelon form of the extended matrix $(a\mid b_i)$, where $b_i$ represents the vectors $\begin{pmatrix}1 \\ 1 \\ 1\end{pmatrix}$ and $\begin{pmatrix}-2 \\ 1 \\ 0\end{pmatrix}$, is necessary to calculate the solution set for both cases. Additionally, they discuss an alternative approach using the identity matrix to simplify the process.

PREREQUISITES
  • Understanding of Gaussian elimination and echelon forms
  • Familiarity with matrix notation and operations
  • Knowledge of linear algebra concepts, specifically solution sets of linear systems
  • Experience with extended matrices and identity matrices
NEXT STEPS
  • Learn about the implications of echelon forms in solving linear systems
  • Study the properties and applications of extended matrices in linear algebra
  • Explore the Gauss-Jordan elimination method for finding solutions
  • Investigate the relationship between echelon forms and matrix inverses
USEFUL FOR

Students, educators, and professionals in mathematics, particularly those studying linear algebra and matrix theory, will benefit from this discussion.

mathmari
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Hey! :o

Let $\displaystyle{a:=\begin{pmatrix}2 & 1 & 0 & 5 \\ 1 & 0 & 1 & 1 \\ 4 & 1 &2 & 7\end{pmatrix}\in \mathbb{R}^{3\times4}}$ and $\displaystyle{b_1:=\begin{pmatrix}1 \\ 1 \\ 1\end{pmatrix} , \ b_2:=\begin{pmatrix}-2 \\ 1 \\ 0\end{pmatrix} \in \mathbb{R}^3}$.

I applied the Gauss algorithm to get the echelon form of the matrix $a$ :
\begin{align*}\begin{pmatrix}2 & 1 & 0 & 5 \\ 1 & 0 & 1 & 1 \\ 4 & 1 &2 & 7\end{pmatrix} & \ \overset{R_2:R_2-\frac{1}{2}\cdot R_1}{\longrightarrow} \ \begin{pmatrix}2 & 1 & 0 & 5 \\ 0 & -\frac{1}{2} & 1 & -\frac{3}{2} \\ 4 & 1 &2 & 7\end{pmatrix} \\ &\ \overset{R_3:R_2-2\cdot R_1}{\longrightarrow} \ \begin{pmatrix}2 & 1 & 0 & 5 \\ 0 & -\frac{1}{2} & 1 & -\frac{3}{2} \\ 0 & -1 &2 & -3\end{pmatrix}\\ &\ \overset{R_3:R_2-2\cdot R_2}{\longrightarrow} \ \begin{pmatrix}2 & 1 & 0 & 5 \\ 0 & -\frac{1}{2} & 1 & -\frac{3}{2} \\ 0 & 0 &0 & 0\end{pmatrix}\end{align*}

Then I want to determine the solution set of the system $ax=b_i$ using the echelon form for $i=1$ and $i=2$.

Does this mean that we can use the echelon form of $a$ to calculate the solution or do we use the echelon form of the extended matrix $(a\mid b_i)$ ? (Wondering)
 
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mathmari said:
Then I want to determine the solution set of the system $ax=b_i$ using the echelon form for $i=1$ and $i=2$.

Does this mean that we can use the echelon form of $a$ to calculate the solution or do we use the echelon form of the extended matrix $(a\mid b_i)$ ?

Hey mathmari!

I'm afraid that we'll have to use the echelon form of the extended matrix $(a\mid b_i)$. (Thinking)

Alternatively we could use the echelon form of the extended matrix $(a\mid I_3)$ where $I_3$ is the 3x3 identity matrix. (Thinking)
 
You can do both problems at once by row reducing
\begin{pmatrix}2 & 1 & 0 & 5 & 1 & -2 \\ 1 & 0 & 1 & 1 & 1 & 1 \\ 4 & 1 & 2 & 7 & 1 & 0\end{pmatrix} where the last two columns are b_1 and b_2.

Klas Van Aarsen's suggestion that you row reduce
\begin{pmatrix}2 & 1 & 0 & 5 & 1 & 0 & 0 \\ 1 & 0 & 1 & 1 & 0 & 1 & 0\\ 4 & 1 & 2 & 7 & 0 & 0 & 1 \end{pmatrix}
uses the fact that once you have row reduced A, the same operations will have converted the identity matrix to A^{-1}.
 

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