Example #1
0
        public double CalculateOutputValue(List <RadialNeuron> radialNeurons)
        {
            double sum = 0;

            for (int i = 0; i < Weights.Count; i++)
            {
                sum += Weights[i] * radialNeurons[i].OutputValue;
            }
            sum        += BiasWeight;
            OutputValue = LinearFunction.F(sum);
            return(OutputValue);
        }
Example #2
0
 public double CalculateGradient(double expectedDataSample)
 {
     Gradient = CalculateError(expectedDataSample) * LinearFunction.Derivative() * 1.0;
     return(Gradient);
 }