Solve Echelon Matrices Homework with Row Operations & Gaussian Elimination

In summary, the conversation discusses finding the general solution to a problem involving row operations and Gaussian elimination. The concept of an echelon matrix or row echelon form is also discussed, with the properties being that all zero rows are at the bottom, the leading entry in each row is 1, and the leading entries move to the right as we move down the rows. There may be exceptions to these properties and sometimes the requirement for a leading entry to be 1 can be ignored.
  • #1
DiamondV
103
0

Homework Statement


Find the general solution
69ca6177fa.png


Homework Equations


Row operations
Gaussian elimination

The Attempt at a Solution


5d39a77963.jpg


This is has happened twice now and I'm not too sure how to deal with it. The last row ends up being all zeros except in that spot. I need to make this into an echelon matrix and for that I need a 1 in the 3rd entry of row 3. Not sure how to get it like that.
 
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  • #2
DiamondV said:

Homework Statement


Find the general solution
69ca6177fa.png


Homework Equations


Row operations
Gaussian elimination

The Attempt at a Solution


5d39a77963.jpg


This is has happened twice now and I'm not too sure how to deal with it. The last row ends up being all zeros except in that spot. I need to make this into an echelon matrix and for that I need a 1 in the 3rd entry of row 3. Not sure how to get it like that.
What is the definition of an echelon matrix or row echelon form?
 
  • #3
Samy_A said:
What is the definition of an echelon matrix or row echelon form?
We say that an m × n matrix is a row echelon matrix if it has the following three properties.
1 All zero rows, if there are any, are at the bottom of the matrix.
2 The leading entry of each non-zero row equals 1.
3 If rows numbered i and i + 1 are two successive non-zero rows, the leading entry of row i + 1 is in a column strictly to the right of the column containing the leading entry of row i.
 
  • #4
DiamondV said:
We say that an m × n matrix is a row echelon matrix if it has the following three properties.
1 All zero rows, if there are any, are at the bottom of the matrix.
2 The leading entry of each non-zero row equals 1.
3 If rows numbered i and i + 1 are two successive non-zero rows, the leading entry of row i + 1 is in a column strictly to the right of the column containing the leading entry of row i.
Correct, although property 2 is not always included, and easily fixed anyway.
Does your last matrix satisfy properties 1 and 3?

Do you notice that these properties do not imply what you wrote in the first post (bolding mine)?
DiamondV said:
This is has happened twice now and I'm not too sure how to deal with it. The last row ends up being all zeros except in that spot. I need to make this into an echelon matrix and for that I need a 1 in the 3rd entry of row 3.
 
  • #5
Samy_A said:
Correct, although property 2 is not always included, and easily fixed anyway.
Does your last matrix satisfy properties 1 and 3?

Do you notice that these properties do not imply what you wrote in the first post (bolding mine)?

For the first condition, there are no zero rows so that satisfied.
It doesn't satisfy property 3, assuming row 2 to be row i and row 3 to be i+1, then I would still need a 1 in the third entry of the row 3 as that is the column to the right of the leading entry of row 2.
 
  • #6
DiamondV said:
For the first condition, there are no zero rows so that satisfied.
It doesn't satisfy property 3, assuming row 2 to be row i and row 3 to be i+1, then I would still need a 1 in the third entry of the row 3 as that is the column to the right of the leading entry of row 2.
No, this is not a correct interpretation of property 3: "If rows numbered i and i + 1 are two successive non-zero rows, the leading entry of row i + 1 is in a column strictly to the right of the column containing the leading entry of row i."
"column strictly to the right of ..." doesn't necessarily mean "first column to the right of ...".
 
  • #7
Samy_A said:
No, this is not a correct interpretation of property 3: "If rows numbered i and i + 1 are two successive non-zero rows, the leading entry of row i + 1 is in a column strictly to the right of the column containing the leading entry of row i."
"column strictly to the right of ..." doesn't necessarily mean "first column to the right of ...".
Hm. I understand what youre saying. In other parts of the notes he says:
Echelon Matrices:
All zero rows are at the bottom
Leading entry in each row is 1
Leading entries are moving to the right as we move down the rows.

So what youre saying is basically at this point in time I can solve that matrix by just make that -3 in row 2 to a 1(not even necessary)?
 
  • #8
DiamondV said:
Hm. I understand what youre saying. In other parts of the notes he says:
Echelon Matrices:
All zero rows are at the bottom
Leading entry in each row is 1
Leading entries are moving to the right as we move down the rows.

So what youre saying is basically at this point in time I can solve that matrix by just make that -3 in row 2 to a 1(not even necessary)?
Yes. Your last matrix is in row echelon form (except for property 2, which you can safely ignore here).
 
  • #9
Samy_A said:
Yes. Your last matrix is in row echelon form (except for property 2, which you can safely ignore here).
Are there like certain weird exceptions to this ? Also when can you not ignore the fact that the leading entry isn't 1?
 
  • #10
DiamondV said:
Are there like certain weird exceptions to this ? Also when can you not ignore the fact that the leading entry isn't 1?
I don't know. As property 2 is often included in the definition, I guess there must be a reason for that.
For solving the system of equations from the bottom up using the row echelon form I don't see what benefit we get from having specifically 1 as leading row entry.

Another take on this:
If you are required to pivot on a one, then you must sometimes use the second elementary row operation and divide a row through by the leading element to make it into a one. Division leads to fractions. While fractions are your friends, you're less likely to make a mistake if you don't use them.

What's the catch? If you don't pivot on a one, you are likely to encounter larger numbers. Most people are willing to work with the larger numbers to avoid the fractions.
 
  • #11
Samy_A said:
I don't know. As property 2 is often included in the definition, I guess there must be a reason for that.
For solving the system of equations from the bottom up using the row echelon form I don't see what benefit we get from having specifically 1 as leading row entry.

Another take on this:
I mean through the entire class, he has always told us to pivot at a 1 in order to make the values below the 1 in that column a 0, and then we move to the second column and pivot at a 1.
 
  • #12
DiamondV said:
I mean through the entire class, he has always told us to pivot at a 1 in order to make the values below the 1 in that column a 0, and then we move to the second column and pivot at a 1.
Maybe you can ask him for the reason.
 
  • #13
DiamondV said:
I mean through the entire class, he has always told us to pivot at a 1 in order to make the values below the 1 in that column a 0, and then we move to the second column and pivot at a 1.

Many discussions of echelon matrices do not require that the leading coefficients in rows are = 1; they are satisfied with having them ≠ 0 (so you can divide by them).
 
  • #14
Are you required to use matrices here? It looks to me like simple "elimination" would work better. For example, adding twice the first equation to the second equation will eliminate both z and w and give 3x+ y= 5 so y= 5- 3x. Putting that into the last equation, -x+ 10- 6x+ 3z= 10- 7x+ 3z= 4 so 3z= -6+ 7x so z= -2+ (7/3)x. Finally, putting both y= 5- 3x and z= -2+ (7/3)x into the first equation gives x+ 5- 3x- 2+ (7/3)x- w= (1/3)x+ 3- w= 4 so w= 1- (1/3)x. Since you have only three equations in four unknowns, the "general solution" will be three of the unknowns in terms of the fourth.
 

1. What is the purpose of solving echelon matrices with row operations and Gaussian elimination?

The purpose of solving echelon matrices with row operations and Gaussian elimination is to simplify and rearrange a system of linear equations in order to find the solution. This method is used to reduce a system of equations to its simplest form, making it easier to solve and understand.

2. How do row operations and Gaussian elimination work together to solve echelon matrices?

Row operations involve using elementary row operations, such as multiplying a row by a scalar, adding a multiple of one row to another, and swapping rows, to manipulate the equations and simplify the matrix. Gaussian elimination is a specific method of using row operations to reduce a matrix to echelon form. Together, these techniques help to solve the system of equations.

3. What are the steps involved in solving echelon matrices with row operations and Gaussian elimination?

The steps for solving echelon matrices with row operations and Gaussian elimination are:

  1. Write the system of equations in matrix form.
  2. Use elementary row operations to reduce the matrix to echelon form.
  3. Use back substitution to solve for the values of the variables.
  4. Check the solution by substituting the values back into the original equations.

4. Is there a specific order in which row operations should be performed?

Yes, there is a specific order in which row operations should be performed. This order is known as the pivot method and involves moving from left to right, starting with the first column, and then moving down to the next row.

5. What are some common mistakes to avoid when solving echelon matrices with row operations and Gaussian elimination?

Some common mistakes to avoid when solving echelon matrices with row operations and Gaussian elimination are:

  • Forgetting to perform row operations in the correct order.
  • Not keeping track of the operations performed and making errors in calculations.
  • Not simplifying fractions when using the pivot method.
  • Accidentally performing an incorrect row operation, such as adding instead of subtracting.

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