static void Main(string[] args)
{
double[,] weightsMatrix = new double[PerceptronConfig.NumberOfNeurons, PerceptronConfig.NumberOfInputs]
{
{ 0.5, 0.7 },
{ 0.8, 0.3 },
};
double[] biases = { -0.1, 0.2 };
Perceptron perceptron = new Perceptron(weightsMatrix, biases);
Random rnd = new Random();
StringBuilder inputsAccumulator = new StringBuilder(5);
double[][] inputsMatrix = new double[NumberOfTests][];
for (int i = 0; i < NumberOfTests; i++)
{
inputsMatrix[i] = new double[PerceptronConfig.NumberOfInputs];
for (int j = 0; j < PerceptronConfig.NumberOfInputs; j++)
{
var randomNumberInRange =
rnd.NextDouble() * (PerceptronConfig.UpperInputValueBound -
PerceptronConfig.LowerInputValueBound) + PerceptronConfig.LowerInputValueBound;
inputsMatrix[i][j] = randomNumberInRange;
inputsAccumulator.Append($"{randomNumberInRange} ");
}
Console.WriteLine($"\nInput set {i + 1}: {inputsAccumulator}");
perceptron.CalculateActivations(inputsMatrix[i]);
inputsAccumulator.Clear();
}
}
public Network(int sizex, int sizey, List <Bitmap> weightNeuron)
{
percept = new Perceptron[10];
for (int i = 0; i < 10; i++)
{
percept[i] = new Perceptron(sizex, sizey, i.ToString(), weightNeuron[i]);
}
}
