NN_test.rar_MLP

#include <stdlib.h> #include <stdio.h> #include <time.h> #include <math.h> #include <fstream> #include <iostream> #include <float.h> #include <conio.h> using namespace std; #define In_number 64 #define Pats_number 5 #define Out_number 5 #define HN_number 10 const double Etta_H = 0.06; const double Etta_O = 0.06; void W_initialize(); void Pattern_load(); void NN_calculation(); void Test_Er_calculation(); int Pattern_Index = 0; double Er_pat[Out_number]; double Out_pat[Out_number]; double Error = 0.0; double Neuron_out[HN_number]; double W_H[In_number][HN_number]; double W_O[HN_number][Out_number]; double Teta_H[HN_number]; double Teta_O[Out_number]; int In_trainData[Pats_number][In_number]; int Out_trainData[Pats_number][Out_number]; void NN_calculation(void) { int i,j = 0; for(i = 0;i<HN_number;i++) { Neuron_out[i] = Teta_H[i]; for(int j = 0;j<In_number;j++) { Neuron_out[i] = Neuron_out[i] + (In_trainData[Pattern_Index][j] * W_H[j][i]); } Neuron_out[i] = tanh(Neuron_out[i]); // tanh function as hidden neuron function // Neuron_out[i] = 1/(1 + exp(-Neuron_out[i])); // Sigmoid function as hidden neuron function } for (i = 0;i<Out_number;i++) { Out_pat[i] = Teta_O[i]; Er_pat[i] = 0; } for (i = 0;i<Out_number;i++) { for(j = 0;j<HN_number;j++) { Out_pat[i] = Out_pat[i] + Neuron_out[j] * W_O[j][i]; } } for (i = 0;i<Out_number;i++) Er_pat[i] = Out_pat[i] - Out_trainData[Pattern_Index][i]; } void loadWeights(void) { FILE *pFile; const char* strFileName = "Optimum_weights.txt"; errno_t err; if( (err = fopen_s( &pFile, strFileName, "r" )) !=0) printf( "Error loading file '%s' - file does not exist" ); else printf( "\nThe file 'Optimum_weights.txt' was opened\n" ); printf("Loading weights ...\n\n"); for(int j = 0;j<HN_number;j++) { for(int i = 0;i<In_number;i++) { fscanf_s (pFile , "%lg", &(W_H[i][j]) ); } } for(int j = 0;j<HN_number;j++) { fscanf_s (pFile , "%lg", &(Teta_H[j])); } for(int i = 0;i<Out_number;i++) { for(int j = 0;j<HN_number;j++) { fscanf_s (pFile , "%lg", &(W_O[j][i])); } } for(int i = 0;i<Out_number;i++) { fscanf_s (pFile , "%lg", &(Teta_O[i])); } fclose(pFile); } void loadTest(void) { FILE *pFile; int i,j; const char* strFileName = "Test_data.txt"; errno_t err; if( (err = fopen_s( &pFile, strFileName, "r" )) !=0) printf( "Error loading file '%s' - file does not exist" ); else printf( "\nThe file 'Test_results.txt' was created\n" ); for (i = 0; i < Pats_number; i++ ) { for ( j = 0; j < In_number; j++ ) { //nNumberOfFields = fscanf_s (pFile , "%lg %lg", &dX , &dY ); fscanf_s (pFile , "%d", &(In_trainData[i][j]) ); // In_trainData[i][j] = Input[j][i]; } for (j = 0; j < Out_number; j++ ) { fscanf_s (pFile , "%d", &(Out_trainData[i][j]) ); } } fclose(pFile); } void Test_Er_calculation(void) { Error = 0.0; //for(int i = 0;i<Pats_number;i++) for(int j = 0;j<Out_number;j++) { //Pattern_Index = i; NN_calculation(); Error = Error + (Er_pat[j] * Er_pat[j]); } } int main(void) { loadWeights(); loadTest(); ofstream OutF1("Test_results.txt"); OutF1 << "Outputs results for the test patterns" <<endl; OutF1 << "-------------------------------------" <<endl; OutF1 << "Pattern" << " " << "Error " << " " << "Neural Netwok Outputs" <<endl; OutF1 << "-------" << " " << "---------" << " " << "---------------------" <<endl; for(int i = 0;i<Pats_number;i++) { OutF1 << i <<" "; Pattern_Index = i; Test_Er_calculation(); OutF1 << Error << " "; for(int j = 0;j<Out_number;j++) { NN_calculation(); OutF1 << Out_pat[j] <<" "; } OutF1 << endl; } getch(); return 0; }