#include<stdio.h>
#include<stdlib.h>
#include<math.h>
#include<conio.h>
void main(void)
{
int K, P, C, J;
double A[100][101];
int N;
int Row[100];
double X[100];
double SUM, M;
int T;
do
{
printf("Please enter number of equations [Not more than %d]\n",100);
scanf("%d", &N);
} while( N > 100);
printf("You say there are %d equations.\n", N);
printf("From AX = B enter elements of [A,B] row by row:\n");
for (K = 1; K <= N; K++)
{
for (J = 1; J <= N+1; J++)
{
printf(" For row %d enter element %d please :\n", K, J);
scanf("%lf", &A[K-1][J-1]);
}
}
for (J = 1; J<= N; J++) Row[J-1] = J - 1;
for (P = 1; P <= N - 1; P++)
{
for (K = P + 1; K <= N; K++)
{
if ( fabs(A[Row[K-1]][P-1]) > fabs(A[Row[P-1]][P-1]) )
{
T = Row[P-1];
Row[P-1] = Row[K-1];
Row[K-1] = T;
}
}
if (A[Row[P-1]][P-1] 0)
{
printf("The matrix is SINGULAR !\n");
printf("Cannot use algorithm --- exit\n");
exit(1);
}
X[N-1] = A[Row[N-1]][N] / A[Row[N-1]][N-1];
for (K = N - 1; K >= 1; K--)
{
SUM = 0;
for (C = K + 1; C <= N; C++)
{
SUM += A[Row[K-1]][C-1] * X[C-1];
}
X[K-1] = ( A[Row[K-1]][N] - SUM) / A[Row[K-1]][K-1];
}
for( K = 1; K <= N; K++)
printf("X[%d] = %lf\n", K, X[K-1]);
getch();
}
Of course, Gaussian Elimination!
Gaussian elimination is used to solve systems of linear equations.
gauss
The gaussian elimination is used to solve many linear equations with many unknown varaibles at once. [See related link below to find out how to do it]. This is used alot by engineers you know ceratin variables in there structures and want to find out what the stress and strain is in certain areas. They make up there linear equations and then they can use the gaussian elimination method to find the unknown variables.
It solves a system of equations. Think of the 2X2 case of having X+Y=1 and 3X+2Y=6.
Of course, Gaussian Elimination!
Gaussian elimination is used to solve systems of linear equations.
none
gauss
The gaussian elimination is used to solve many linear equations with many unknown varaibles at once. [See related link below to find out how to do it]. This is used alot by engineers you know ceratin variables in there structures and want to find out what the stress and strain is in certain areas. They make up there linear equations and then they can use the gaussian elimination method to find the unknown variables.
Gaussian elimination as well as Gauss Jordan elimination are used to solve systems of linear equations. If, using elementary row operations, the augmented matrix is reduced to row echelon form, then the process is called Gaussian elimination. If the matrix is reduced to reduced row echelon form, the process is called Gauss Jordan elimination. In the case of Gaussian elimination, assuming that the system is consistent, the solution set can be obtained by back substitution whereas, if the matrix is in reduced row echelon form, the solution set can usually be obtained directly from the final matrix or at most by a few additional simple steps.
It solves a system of equations. Think of the 2X2 case of having X+Y=1 and 3X+2Y=6.
Please visit the related link at the bottom. If I tried to write the computer algorithm here it would get very messy.
The Chinese are believed to have started the development of systems of equation. They came up with a system for equation known as Gaussian elimination in 200 BC.
For systems with more than three equations, Gaussian elimination is far more efficient. By using Gaussian elimination we bring the augmented matrix into row-echelon form without continuing all the way to the reduced row-echelon form. When this is done, the corresponding system can be solved by the back-substitution technique.
gaussian
the gaussian filter is also known as Gaussian smoothing and is the result of blurring an image by a Gaussian function.