MLP ODE Timeseries

MLP_ODE_Activation.py

#define sigmoid activation function
def f_sigmoid(value):
    return 1.0/(1.0+np.exp(-value))

def f_sigmoid_derivation(value):
    return f_sigmoid(value)*(1-f_sigmoid(value))
  
#define linear activation function
def f_linear(value):
    return value

def f_linear_derivation(value):
    return np.ones(value.shape, np.float32)
  
  

#hidden layer activation function wrapper
def f_activation(value):
    return f_sigmoid(value)
  
def f_activation_derivation(value):
    return f_sigmoid_derivation(value)

#output layer activation function wrapper
def f_activation_output(value):
    return f_linear(value)

def f_activation_derivation_output(value):
    return f_linear_derivation(value)