class Neuron
{
  float[] weights = new float[2];
  float error;
  double LearningRate;
  Neuron()
  {
    for(int i = 0; i < weights.length; i++)
     weights[i] = random(-1, 1);
    LearningRate = 0.01;
  }

  float guess(int[] inputs)
  {
    float sum = 1;

    for(int i = 0; i < weights.length; i++)
     sum += weights[i]*inputs[i];

    return sum;
  }

  void trynewlr()
  {
   LearningRate = pow(10, floor(random(10))*-1);
   for(int i = 0; i < weights.length; i++)
     weights[i] = random(-1, 1);
  }
  void learn(int[] inputs, int target)
  {
    float guess = guess(inputs);
    if(guess == Float.NaN)
    {
      trynewlr();
      guess = guess(inputs);
    }
    error = target - guess;
    for(int i = 0; i < weights.length; i++)
      weights[i] += error * inputs[i]* LearningRate;
  }
}