//计算梯度，target是目标值，如果有目标值，则是输出节点
public double CalculateGradient(double?target = null)
{
//如果没有目标值，说明是中间层
if (target == null)
{
//return Gradient = OutputSynapses.Sum(a => a.OutputNeuron.Gradient * a.Weight) * Sigmoid.Derivative(OutputValue);
return(Gradient = Error * Sigmoid.Derivative(OutputValue));
}
//如果有目标值，说明是输出层
return(Gradient = Error * Sigmoid.Derivative(OutputValue));
// return Gradient = Sigmoid.Derivative(OutputValue);
}
//计算输出值 ，输入值加上偏置，然后应用sigmoid函数
public virtual double CalculateValue()
{
this.InputValue = InputSynapses.Sum(a => a.Weight * a.InputNeuron.OutputValue);
return(OutputValue = Sigmoid.Output(InputValue + Bias));
}
