How to Solve Linear Equations Using Gaussian Reduction

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In summary, the linear equations 3x+2y-z=5, -2x+2y+5z=2, and x-2y+3z=11 were solved using the Gaussian method. After putting the equations in echelon form and performing the necessary operations, the final row was found to be 0 0 1 2/17. This follows the law that the leading coefficient of each nonzero row is one.
  • #1
kash-k
17
0
3x+2y-z=5
-2x+2y+5z=2
x-2y+3z=11

Now we are required to solve these linear equations via Gaussian method.

I put these in an echelon form and this how I did it:

Switch L1 with L3 to make life easier.

L1: x-2y+3z=11
L2:-2x+2y+5z=2
L3:3x+2y-z=5

Then I went to work to remove eliminate X from L2 and L3.

L2 + 2L1
L3 + (-3L1)

Which got me:

L2: 0 -2 11 23

L3: 0 8 -8 -28

Then I removed the Y from L3.

L3+(4L2)

However, I got a stupid number which didn't follow the law:

The bottom row had to be : 0 0 1 X

So if anyone can help me solve this I'd be much obliged. Thank you
 
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  • #2
kash-k said:
3x+2y-z=5
-2x+2y+5z=2
x-2y+3z=11

Now we are required to solve these linear equations via Gaussian method.

I put these in an echelon form and this how I did it:

Switch L1 with L3 to make life easier.

L1: x-2y+3z=11
L2:-2x+2y+5z=2
L3:3x+2y-z=5

Then I went to work to remove eliminate X from L2 and L3.

L2 + 2L1
L3 + (-3L1)

Which got me:

L2: 0 -2 11 23

L3: 0 8 -8 -28

Then I removed the Y from L3.

L3+(4L2)

However, I got a stupid number which didn't follow the law:

The bottom row had to be : 0 0 1 X

So if anyone can help me solve this I'd be much obliged. Thank you

What do you MEAN by "a stupid number". Following what you did I get, as the last line,
0 0 34 20.

Now divide that line (equation) by 34 to get 0 0 1 10/17.

Doesn't look stupid to me.
 
  • #3
20 is wrong
way wrong
 
  • #4
kash-k said:
3x+2y-z=5
-2x+2y+5z=2
x-2y+3z=11

Now we are required to solve these linear equations via Gaussian method.

I put these in an echelon form and this how I did it:

Switch L1 with L3 to make life easier.

L1: x-2y+3z=11
L2:-2x+2y+5z=2
L3:3x+2y-z=5

Then I went to work to remove eliminate X from L2 and L3.

L2 + 2L1
L3 + (-3L1)

Which got me:

L2: 0 -2 11 23

L3: 0 8 -8 -28
You are right. I just copied your error. L3- 3L1 gives 3-3(1)= 0, 2- 3(-2)= 8, -1-3(3)= -10, 5- 3(11)= -28. That last line should be
0 8 -10 -28.

Then I removed the Y from L3.

L3+(4L2)
Now L3+ 4L2 is 8+ 4(-2)= 0, -10+ 4(11)= 34, -28+ 4(24)= 68.[/quote]
Looks like 0 0 34 68

However, I got a stupid number which didn't follow the law:

The bottom row had to be : 0 0 1 X

So if anyone can help me solve this I'd be much obliged. Thank you
Now divide the last row by 34. By the way, which "law" are you referring to? No matter what numbers you get in the last two places, you can always divide by the "z" coefficient to get "0 0 1 X".
 
  • #5
I guess at the end of the day it was a calculating mistake on my part.

And for the law I misunderstood. "The leading coefficient of each nonzero row is one"

Thank you for the help.

Regards

ps. so the last row is 0 0 1 2
 

1. What is Gaussian reduction?

Gaussian reduction is a mathematical method used to solve a system of linear equations by transforming it into an equivalent system with a simpler form. It involves eliminating variables from the equations until only one unknown remains in each equation, making it easier to find the solution.

2. How is Gaussian reduction performed?

Gaussian reduction is performed by using elementary row operations on a matrix that represents the system of equations. These operations include multiplying rows by a constant, adding rows together, and swapping rows. The goal is to transform the matrix into row-echelon form, where the coefficients of the variables form an upper triangular matrix.

3. What is the purpose of Gaussian reduction?

The purpose of Gaussian reduction is to simplify a system of linear equations so that it can be solved more easily. This method can be used to find the solution to a system of equations, determine if the system has a unique solution, or prove that the system has no solution.

4. Can Gaussian reduction be used for any system of linear equations?

Yes, Gaussian reduction can be used for any system of linear equations. However, it may not always be the most efficient method for solving the system, as the number of elementary row operations needed can vary. Other methods, such as Cramer's rule or matrix inversion, may be more suitable for certain types of systems.

5. Are there any limitations to using Gaussian reduction?

One limitation of Gaussian reduction is that it can be time-consuming for large systems of equations. Additionally, if the matrix representing the system is ill-conditioned, meaning it is close to being singular, the calculations may be prone to errors. In these cases, other methods may be more accurate and efficient.

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