Finding limitations for matrix

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In summary: Do you know how the person who answered the question came to their conclusion? In summary, the solution to finding all matrices X such that A\cdot X = A' with the 2nd and 4th column swapped is to use matrix column operations. This method allows you to solve for X in a systematic way and does not depend on any assumptions about the values of the elements in X. In this case, the resulting matrix X is the identity matrix with the 2nd and 4th column swapped.
  • #1
nuuskur
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Homework Statement


Let [itex]A\in Mat_{3,4}(K)[/itex]. Find all matrices X such that [itex]\forall X| A\cdot X = A'[/itex], where A' is the same as A with 2nd and 4th column swapped.

Homework Equations

The Attempt at a Solution


First we determine the size of matrix X. By definition the first factor must have as many columns as the second has rows and the end product is [itex]A_{m,n}\cdot B_{n,p} = C_{m,p}[/itex]. X must be 4 x 4. Let [itex]a'_{i,j}\in A', a_{i,j}\in A[/itex]

Haven't been able to (in my opinion) come up with anything sensible. Essentially, I have noticed that if we denote rows of A and columns of X as vectors, such that [itex]a_1 = (a_{1,1},a_{1,2},a_{1,3},a_{1,4})[/itex](by row up to a3) and [itex]x_1 = (x_{1,1},x_{2,1},x_{3,1},x_{4,1})[/itex](by column up to x4)
Then the dot products equal to the corresponding element of A except when we multiply by either x2 or x4. Problem is, where do I find the conditions for matrix X?
I can also write out the dot products individually, but then I have 3 equations and 4 variables..

I have concluded that:
[tex]
\begin{cases}
a'_{i,j} = a_{i,j}= \sum_{k=1}^4 a_{i,k}\cdot x_{k,j},& j\in\{1,3\}\\
a'_{i,2} = \sum_{k=1}^4 a_{i,k}\cdot x_{k, 2} = a_{i,4}\\
a'_{i,4} = \sum_{k=1}^4 a_{i,k}\cdot x_{k, 4} = a_{i,2}

\end{cases}

[/tex]
THIS LOOKS UGLY! I can't think of any other way to show conditions for all x in X :s
This definitely is not acceptable, suggestions?

(I want to avoid writing out individual x - what if the dimensions of the matrix are countible? Would take a long time to write them out xD)
 
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  • #2
If X were the identity matrix it would look like this: [itex]
\begin{matrix}
1 & 0 & 0 & 0 \\
0 & 1 & 0 & 0\\
0 & 0 & 1 & 0 \\
0 & 0 & 0 & 1 \\
\end{matrix}[/itex]. The second row controls the second column in the product, and the fourth row controls the fourth column.
 
  • #3
nuuskur said:

Homework Statement


Let [itex]A\in Mat_{3,4}(K)[/itex]. Find all matrices X such that [itex]\forall X| A\cdot X = A'[/itex], where A' is the same as A with 2nd and 4th column swapped.

Homework Equations

The Attempt at a Solution


First we determine the size of matrix X. By definition the first factor must have as many columns as the second has rows and the end product is [itex]A_{m,n}\cdot B_{n,p} = C_{m,p}[/itex]. X must be 4 x 4. Let [itex]a'_{i,j}\in A', a_{i,j}\in A[/itex]

Haven't been able to (in my opinion) come up with anything sensible. Essentially, I have noticed that if we denote rows of A and columns of X as vectors, such that [itex]a_1 = (a_{1,1},a_{1,2},a_{1,3},a_{1,4})[/itex](by row up to a3) and [itex]x_1 = (x_{1,1},x_{2,1},x_{3,1},x_{4,1})[/itex](by column up to x4)
Then the dot products equal to the corresponding element of A except when we multiply by either x2 or x4. Problem is, where do I find the conditions for matrix X?
I can also write out the dot products individually, but then I have 3 equations and 4 variables..

I have concluded that:
[tex]
\begin{cases}
a'_{i,j} = a_{i,j}= \sum_{k=1}^4 a_{i,k}\cdot x_{k,j},& j\in\{1,3\}\\
a'_{i,2} = \sum_{k=1}^4 a_{i,k}\cdot x_{k, 2} = a_{i,4}\\
a'_{i,4} = \sum_{k=1}^4 a_{i,k}\cdot x_{k, 4} = a_{i,2}

\end{cases}

[/tex]
THIS LOOKS UGLY! I can't think of any other way to show conditions for all x in X :s
This definitely is not acceptable, suggestions?

(I want to avoid writing out individual x - what if the dimensions of the matrix are countible? Would take a long time to write them out xD)

Google 'matrix column operations'; for example, see
http://stattrek.com/matrix-algebra/elementary-operations.aspx
or
https://unapologetic.wordpress.com/2009/08/27/elementary-row-and-column-operations/

These show explicitly how to find the matrix X. (They leave unanswered the question of whether X is unique---they just show how to find one possible X.)
 
  • #4
Okay, if I approach this deductively, then
[itex]a'_{11} = a_{11}\cdot x_{11} + a_{12}\cdot x_{21} + a_{13}\cdot x_{31} + a_{14}\cdot x_{41} = a_{11} [/itex] if x11 = 1, then the other three summands would sum to 0 and the resulting matrix is very similar to the identity matrix, BUT
x11 does not have to be 1 in which case everything breaks.

Intuitively I am quite sure that the X is the identity matrix with 2, 4 column swapped - but this is all deduction based math. I am not satisfied.
 
  • #5
nuuskur said:
Okay, if I approach this deductively, then
[itex]a'_{11} = a_{11}\cdot x_{11} + a_{12}\cdot x_{21} + a_{13}\cdot x_{31} + a_{14}\cdot x_{41} = a_{11} [/itex] if x11 = 1, then the other three summands would sum to 0 and the resulting matrix is very similar to the identity matrix, BUT
x11 does not have to be 1 in which case everything breaks.

Intuitively I am quite sure that the X is the identity matrix with 2, 4 column swapped - but this is all deduction based math. I am not satisfied.

What is unsatisfactory about it? What is wrong with building on past knowledge developed by others?
 

Related to Finding limitations for matrix

What does "finding limitations for matrix" mean?

Finding limitations for matrix refers to the process of identifying and analyzing the constraints or restrictions that may affect a matrix in a scientific experiment or study. These limitations can include factors such as sample size, measurement accuracy, and external influences on the data.

Why is it important to find limitations for a matrix?

Identifying limitations for a matrix is crucial in order to properly interpret and draw conclusions from the data. By understanding the potential constraints, scientists can adjust their analysis and account for these factors, leading to more accurate and reliable results.

How do you determine the limitations for a matrix?

There are several methods for identifying limitations for a matrix. One approach is to thoroughly examine the experimental design and potential sources of error or bias. Another method is to conduct sensitivity analysis, which involves varying the parameters of the matrix to see how sensitive the results are to different inputs.

What are some common limitations for matrices?

Common limitations for matrices include small sample size, measurement error, confounding variables, and selection bias. Other factors such as equipment limitations, human error, and environmental factors can also impact the accuracy and reliability of matrix data.

Can limitations for a matrix be overcome?

In some cases, limitations for a matrix can be addressed or minimized through careful experimental design, data analysis techniques, and statistical methods. However, some limitations may be inherent and cannot be completely eliminated. It is important for scientists to acknowledge and address these limitations in their research to ensure the validity of their findings.

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