void
train_network(int num)
{
int i, h, o;
unsigned int n;
for(n = 0; n < num; n++) {
init_pattern();
calculate_network();
calculate_errors();
for(h=0; h < NUM_HIDDEN; h++)
for(o=0; o < NUM_OUTPUT; o++)
W_HIDDEN_OUT(h, o) += (((learn * N_HIDDEN(h)) / 1024) * E_OUT(o)) / 1024;
for(i=0; i < NUM_INPUT; i++)
for(h=0; h < NUM_HIDDEN; h++)
W_IN_HIDDEN(i, h) += (((learn * N_IN(i)) / 1024) * E_HIDDEN(h)) / 1024;
}
return;
}
int main(int argc, char const *argv[])
{
printf("Sigma: %f\n", SIGMA);
if (SIGMA > 0.5 )
{
printf("Sigma must be not greater than 0.5 \n");
exit(1);
}
double** numerical_result = calculate_numerical_result();
double** exact_result = calculate_exact_result();
double** errors = calculate_errors(numerical_result, exact_result);
double avg = calculate_average_error(errors);
printf("\nNUMERICAL\n\n\n");
// print_matrix(numerical_result, T_GRID_SIZE, X_GRID_SIZE);
printf("\nEXACT\n\n\n");
// print_matrix(exact_result, T_GRID_SIZE, X_GRID_SIZE);
printf("\nERRORS\n\n\n");
// print_matrix(errors, T_GRID_SIZE, X_GRID_SIZE);
printf("\nAVERAGE ERROR: %lf\n\n", avg);
free_matrix(&numerical_result, T_GRID_SIZE);
free_matrix(&exact_result, T_GRID_SIZE);
free_matrix(&errors, T_GRID_SIZE);
return 0;
}
