Translate the following C++ code into functioning C code. I will repost this que

Question

Translate the following C++ code into functioning C code. I will repost this question so you may get more points..

//Program to illustrate the perceptron training rule

#include <iostream>

#include <cstdlib>

#include <ctime>

#include <cmath>

using namespace std;

int

main()

{

      float w [3]; //array to hold perceptron weights

      float t, o;

      const double eta = .1;

      int i;

      int count = 0;

     

      bool correct = 0;

      //define and initialize training data

      int train [4] [3] = {   0, 0, 0,

                                          0, 1, 0,

                                          1, 0, 0,

                                          1, 1, 1 };

      int x0, x1, x2; //will hold the inputs

      float weightsum, deltaw1, deltaw2;

     

      //initialize random number generator

      srand((unsigned)(time(0)));

      rand();

           

      //initialize threshold

      x0 = -1;

     

     

      w[0] = fabs((float)(rand())/(32767/2)-1);

     

      for ( i = 1; i < 3; ++i)

            w[i] = (float)(rand())/(32767/2) - 1;

      cout << "INITIAL WEIGHTS" << endl

             << "---------------" << endl;

           

      cout << "w0 = " << w[0] << endl;

      cout << "w1 = " << w[1] << endl;

      cout << "w2 = " << w[2] << endl;

     

      //implement perceptron training rule as long as training examples are

      //classified incorrectly

      while(!correct)

      {

            correct = 1;

            count++;

            for (i = 0; i < 4; ++i)

            {

                  x1 = train[i][0]; //input for x1

                  x2 = train[i][1]; //input for x2

                  //find weighted sum of inputs and threshold values

                  weightsum = x0 * w[0] + x1 * w[1] + x2 * w[2];

                  //determine output of perceptron

                  if (weightsum > 0) o = 1;

                  else o = 0;

                  //determine true ouput

                  t = train[i][2];

                 

                  //if the ouput is incorrect adjust the weights.

                  if (o != t)

                  {

                        deltaw1 = eta * (t - o) * x1;

                        w[1] = w[1] + deltaw1;

                        deltaw2 = eta * (t - o) * x2;

                        w[2] = w[2] + deltaw2;

                        correct = 0;

                                         

                  }

            }

      }

      //OUTPUT

      cout << endl << endl;

      cout << "FINAL WEIGHTS" << endl

             << "-------------" << endl;

      cout << "w0 = " << w[0] << endl;

      cout << "w1 = " << w[1] << endl;

      cout << "w2 = " << w[2] << endl;

     

      cout << "The delta rules were invoked " << count << " times"<<endl;

      return 0;

}

Explanation / Answer

#include #include #include #include int main() { float w [3]; //array to hold perceptron weights float t, o; const double eta = .1; int i; int count = 0; int correct = 0; //define and initialize training data int train [4] [3] = { 0, 0, 0, 0, 1, 0, 1, 0, 0, 1, 1, 1 }; int x0, x1, x2; //will hold the inputs float weightsum, deltaw1, deltaw2; //initialize random number generator srand((unsigned)(time(0))); rand(); //initialize threshold x0 = -1; w[0] = fabs((float)(rand())/(32767/2)-1); for ( i = 1; i < 3; ++i) w[i] = (float)(rand())/(32767/2) - 1; printf("INITIAL WEIGHTS "); printf("--------------- "); printf("w0 = %f ", w[0]); printf("w1 = %f ", w[1]); printf("w2 = %f ", w[2]); //implement perceptron training rule as long as training examples are //classified incorrectly while(!correct) { correct = 1; count++; for (i = 0; i < 4; ++i) { x1 = train[i][0]; //input for x1 x2 = train[i][1]; //input for x2 //find weighted sum of inputs and threshold values weightsum = x0 * w[0] + x1 * w[1] + x2 * w[2]; //determine output of perceptron if (weightsum > 0) o = 1; else o = 0; //determine true ouput t = train[i][2]; //if the ouput is incorrect adjust the weights. if (o != t) { deltaw1 = eta * (t - o) * x1; w[1] = w[1] + deltaw1; deltaw2 = eta * (t - o) * x2; w[2] = w[2] + deltaw2; correct = 0; } } } //OUTPUT printf(" "); printf("FINAL WEIGHTS "); printf("------------- "); printf("w0 = %f ", w[0]); printf("w1 = %f ", w[1]); printf("w2 = %f ", w[2]); printf("The delta rules were invoked %d times ", count); return 0; }

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