#include #include #include #include #include using namespace std; /*L1 - W1 - L2 \ W2 L3 W3 \ L1 - W1 - L2 - result W2 L3 W3 / L1 - W1 - L2. / */ void how2timer(int ms) { //code delay function int CLOCKS_PER_MSEC = CLOCKS_PER_SEC / 1000; clock_t end_time = clock() + ms * CLOCKS_PER_MSEC ; // время завершения while (clock() < end_time) {} // цикл ожидания времени // сообщение о конце работы функции } double random(double l1,double l2) { //random number to width matrices return l1 + ((double)rand()/ RAND_MAX)*(l2-l1); } int main() { double err; int x; int y; int generation = 1; //num of cycles int timer = 100; //time of delay double errOut = 1; //error double result = 0; //result neurons double Tresult; //required result double K = 0.00001; double W1[3][3] = {{random(-0.5, 0.5),random(-0.5, 0.5),random(-0.5, 0.5)},{random(-0.5, 0.5),random(-0.5, 0.5),random(-0.5, 0.5)},{0.3,-0.1,0.5}}; double W2[2][2] = {{random(-0.5, 0.5),random(-0.5, 0.5)},{random(-0.5, 0.5),random(-0.5, 0.5)}}; double W3[2][1] = {{random(-0.5, 0.5)},{random(-0.5, 0.5)}}; //witdh matrices double L1[2][3] = {{0,0,0},{0,0,0}}; double L2[2][3] = {{0,0,0},{0,0,0}}; double L3[2][2] = {{0,0},{0,0}}; //neuron error and y value cout << "Start Learning \n"; x = 0; y = 0; while(generation <1000) { result = 0; errOut = 0; how2timer(timer); //start timer L1[0][0] = 100; L1[1][0] = 50; Tresult = rand() % 2; if(Tresult == 1) { Tresult = 0.8; L1[2][0] = L1[0][0] - L1[1][0]; } else { Tresult = 0.2; L1[2][0] = L1[0][0] + L1[1][0]; } cout << "\n 1 num is "<< L1[0][0] << "\n 2 num is " << L1[1][1] << "\n True result is " << Tresult <<"\n Fist Layer complete"; //first three neurons to second three neurons data write x = 0; y = 0; while(y

neural network