示例#1
0
        /// <summary>
        /// Creating a equialent matrix
        /// </summary>
        /// <returns></returns>
        public static bool[,] some()
        {
            bool[,] temp = new bool[8, 8];
            VectorGenerator vg = new VectorGenerator();

            for (int i = 0; i < 8; i++)
            {
                int c = 0;
                foreach (bool k in vg.CreateVector(4))
                {
                    temp[c, i] = k;
                    c++;
                }
            }
            // Displays matrix of input vectors
            for (int i = 0; i < 8; i++)
            {
                // columns
                for (int k = 0; k < 8; k++)
                {
                    Console.Write(Convert.ToInt32(temp[i, k]).ToString() + " ");
                }
                Console.Write('\n');
            }
            bool[,] ttm = new bool[8, 28];
            int ctr = 0;

            // Creates equi matrix
            for (int i = 0; i < 8; i++)
            {
                // columns
                for (int k = 0; k < 8; k++)
                {
                    for (int y = k + 1; y < 8; y++)
                    {
                        ttm[i, ctr] = temp[i, k] == temp[i, y];
                        ctr++;
                    }
                }
                ctr = 0;
            }
            // Displays equi matrix
            for (int i = 0; i < 8; i++)
            {
                for (int k = 0; k < 28; k++)
                {
                    Console.Write(Convert.ToInt32(ttm[i, k]).ToString() + " ");
                }
                Console.Write('\n');
            }
            return(ttm);
        }
示例#2
0
        static void Main(string[] args)
        {
            int               numberOfProps = 5;
            Tree              tree          = new Tree();
            VectorGenerator   vg            = new VectorGenerator();
            NeuronGraph <int> neurons       = new NeuronGraph <int>();

            /****************
             * Very important, below we are instantiating neurons as input level and
             * their indexes are equal to the indexes of features they presenting
             *****************/
            for (int i = 0; i < numberOfProps; i++)
            {
                neurons.AddVertex(neurons.Matrix.VertexCounter);
            }

            // Vector of weights according to neurons
            float[] weights = new float[numberOfProps];
            // Initializing
            for (int i = 0; i < weights.Length; i++)
            {
                weights[i] = 0.1f;
            }
            // Calibrating weights
            for (int i = 0; i < 1000; i++)
            {
                List <bool> input       = vg.CreateVector(numberOfProps);
                float[]     tempWeights = weights;
                for (int k = 0; k < weights.Length; k++)
                {
                    tempWeights[k] = Func(input, weights, k);
                }
                weights = tempWeights;
            }
            foreach (float f in weights)
            {
                Console.WriteLine(f);
            }

            /*********
             * Below is implementation of another algorythm which uses tree
             * **********/

            // Simple loop of vectors input

            /*List<bool> t;
             * for (int i = 0; i < 0; i++)
             * {
             *  // Vectror processing by tree
             *  tree.Add(vg.CreateVector(numberOfProps));
             *  // Checks for activated vertices
             *  t = tree.CheckOver(tree.Root);
             *  // Then creating a new Neuron if activated
             *  if (t != null)
             *  {
             *      Console.WriteLine("Start");
             *      foreach (bool k in t)
             *      {
             *          Console.WriteLine(Convert.ToInt32(k));
             *      }
             *      Console.WriteLine("End");
             *      int currentIndex = neurons.Matrix.VertexCounter;
             *      neurons.AddVertex(currentIndex);
             *      // Inherits from features
             *      for(int counter = 0; counter < t.Count; counter++)
             *      {
             *          neurons.MakeNeighbours(currentIndex, counter);
             *      }
             *  }
             * }
             * //neurons.Matrix.Display();
             * bool[,] ttmm = some();
             * for (int i = 0; i < 28; i++)
             * {
             *  List<bool> tmp = new List<bool>();
             *  for(int k = 0; k<8; k++)
             *  {
             *      tmp.Add(ttmm[k, i]);
             *  }
             *  // Vectroe processing by tree
             *  tree.Add(tmp);
             *  // Checks for activated vertices
             *  t = tree.CheckOver(tree.Root);
             *  // Then creating a new Neuron if activated
             *  if (t != null)
             *  {
             *      Console.WriteLine("Start");
             *      foreach (bool k in t)
             *      {
             *          Console.WriteLine(Convert.ToInt32(k));
             *      }
             *      Console.WriteLine("End");
             *      int currentIndex = neurons.Matrix.VertexCounter;
             *      neurons.AddVertex(currentIndex);
             *      // Inherits from features
             *      for (int counter = 0; counter < t.Count; counter++)
             *      {
             *          neurons.MakeNeighbours(currentIndex, counter);
             *      }
             *  }
             * }*/
        }