Scilab/C4/LinearequationsGaussianMethods/English
Title of script: Solving System of Linear Equations using Gauss Elimination and GaussJordan Methods
Author: Shamika
Keywords: System of linear equations, Gaussian Methods



Slide 1  Dear Friends,
Welcome to the Spoken Tutorial on “Solving System of Linear Equations using Gauss Elimination and GaussJordan Methods” 
Slide 2 Learning Objective Slide  At the end of this tutorial, you will learn how to:

Slide 3System Requirement slide  To record this tutorial, I am using

Slide 4 Prerequisites slide  To practise this tutorial, a learner

Slide 5 System of Linear Equations  A system of linear equations is a

Slide 7 Gaussian Elimination Method  Let us study Gauss elimination method
Given a system of equations

Slide 8 Gaussian Elimination Method 

Slide 9 Gaussian Elimination Method

How do we convert the augmented matrix to an upper triangular form matrix?

Slide 10 Example  Let us solve this system of equations using Gaussian elimination method 
Switch to Scilab and open naivegaussianelimination.sci  Before we solve the system, let us go through the code for Gaussian elimination method. 
Highlight format e comma twenty  The first line of the code is format e comma twenty.

Point to e  The letter 'e' within single quotes denotes that the answer should be displayed in scientific notation 
Point to twenty  The number twenty is the number of digits that should be displayed. 
Highlight funcprot  The command funcprot is used to let Scilab know what to do when variables are redefined. 
Point to zero  The argument zero specifies that Scilab need not do anything if the variables are redefined. 
No visual clue. This is extra information that is being offered to the listener.  Other arguments are used to issue warnings or errors if the variables are redefined. 
Highlight input  Next we use the input function. 
Highlight input

It will display a message to the user and get the values of A and B matrices.

The matrices that the user enters, will be stored in the variables A and b.  
Highlight A
Highlight B 
Here A is the coefficient matrix and b is the righthandside matrix or the constants matrix. 
Highlight naivegaussianelimination  Then we define the function naive gaussian elimination. 
Highlight A
Highlight b 
And we state that A and b are the arguments of the function naive gaussian elimination. 
Highlight x  We store the output in variable x. 
Highlight size  Then we find the size of matrices A and b using the size command. 
Highlight n and n one  Since they are two dimensional matrices, we use n and n one to store the size of matrix A. 
Highlight m one and p  Similarly we can use m one and p for matrix b. 
Highlight
if n ~= n1 error('gaussianelimination  Matrix A must be square'); 
Then we have to determine

Highlight
elseif n ~= m1 error('gaussianelimination  incompatible dimension of A & b'); 
If n and m one are not equal, we display a message
incompatible dimension of A and b. 
Highlight
C=[A b]; 
If the matrices are compatible, we place matrices A and b in one matrix, C.

Highlight
n=size(A,1); for k=1:n1 for i=k+1:n factor=A(i,k)/A(k,k); for j=k+1:n A(i,j)=A(i,j)factor*A(k,j); end b(i)=b(i)factor*b(k); end end 
The next block of code performs forward elimination.
This code converts the augmented matrix to upper triangular matrix form.

Highlight
x(n)=b(n)/A(n,n); for i=n1:1:1 sum=0; for j=i+1:n sum=sum+A(i,j)*x(j); end x(i)=(b(i)sum)/A(i,i); end 

Click on Execute and select Save and Execute  Let us save and execute the file. 
Show Scilab Console  Switch to Scilab console to solve the example. 
Show Scilab Console  On the console, we have a prompt to enter the value of the coefficient matrix.

Type
[3.41 1.23 1.09;2.71 2.14 1.29;1.89 1.91 1.89] 
Type square bracket three point four one space one point two three space minus one point zero nine semi colon
two point seven one space two point one four space one point two nine semi colon one point eight nine space minus one point nine one space minus one point eight nine close square bracket. Press Enter 
Type
[4.72;3.1;2.92] 
The next prompt is for matrix b.
open square bracket four point seven two semi colon three point one semi colon two point nine one close square bracket. Press Enter 
Type
naivegaussianelimination(A,b) 
Then we call the function by typing
naive gaussian elimination open paranthesis A comma b close paranthesis

Show answer on Scilab console  The solution to the system of linear equations is shown on Scilab console. 
Next we shall study the Gauss Jordan method.  
Slide 11 – Gauss Jordan Method  In Gauss – Jordan Method

Slide 12 GaussJordan Method  Then we divide the diagonal element and corresponding element of right hand side element, by the diagonal element.

Slide 13 Example

Let us solve this example using Gauss Jordan Method. 
Switch to Scilab console and open GaussJordan Elimination.sci  Let us look at the code first. 
Highlight
format 
The first line of the code uses format function to specify the format of the displayed answers. 
Highlight
'e' 
The parameter e specifies the answer should be in scientific notation. 
Highlight 20  Twenty (20) denotes that only twenty digits should be displayed. 
Highlight
A=input("Enter the coeffiecient matrix : ") b=input("Enter the righthand side matrix : ") 
Then we get the A and b matrix using the input function. 
Highlight
function [x] = GaussJordanElimination( A, b ) 
We define the function Gauss Jordan Elimination with input arguments A and b and output argument x. 
Highlight
[m, n] = size( A ) 
We get the size of matrix A and store it in m and n 
Highlight
[r, s] = size( b ) 
Similarly, we get the size of matrix b and store it in r and s 
Highlight
if ( m <> r ) then error("Error: matrix A and vector b are incompatible sizes") end 
If the sizes of A and b are not compatible, we display an error on the console using error function. 
Highlight
for k = 1 : 1 : m indices = [ 1 : 1 : k1, k+1 : 1 : m ]
// of the pivoting row to get a zero for i = indices multiplier = C(i, k) / C(k,k) for j = k+1 : n C(i, j) = C(i, j)  multiplier * C(k, j) end end end 
Then we perform row operations to get diagonal form of the matrix.

Highlight
x = zeros( m, s ) 
Then we create a matrix of zeros called x with m rows and s columns. 
Highlight
for i = 1 : 1 : m for j = 1 : 1 : s x(i, j) = C(i, m+j) / C(i, i) end end 
Once we have the diagonal form,

Highlight
x(i, j) = C(i, m+j) / C(i, i) 
We store the value of each variable in x. 
Highlight
return x 
Then we return the value of x.

Highlight
endfunction 
Finally, we end the function. 
Click on Execute and select Save and Execute  Now let us save and execute the function. 
Type the following
[0.7, 1725;0.4352,5.433]

The prompt requires us to enter the value of matrix A.
open square bracket zero point seven comma one seven two five semi colon zero point four three five two comma minus five point four three three close square bracket. Press Enter 
Type the following
[1739;3.271] 
The next prompt is for vector b.
open squre bracket one seven three nine semi colon three point two seven one close square bracket Press Enter 
Type the following
GaussJordanElimination(A,b) 
Then we call the function by typing
Gauss Jordan Elimination open paranthesis A comma b close paranthesis Press Enter 
Show answers on Scilab console  The values of x one and x two are shown on the console. 
Slide 14 Summary  Let us summarize this tutorial.
In this tutorial, we have learnt to:

Show Slide 16
Title: About the Spoken Tutorial Project

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Title: Spoken Tutorial Workshops The Spoken Tutorial Project Team

The Spoken Tutorial Project Team

Show Slide 18
Title: Acknowledgement

* Spoken Tutorial Project is a part of the Talk to a Teacher project

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