GeneralActivationFunction Class Reference
[Neural Network filtering]
The base class for all activation functions in neural network.
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#include <GeneralActivationFunction.h>
Inheritance diagram for GeneralActivationFunction:
Public Member Functions | |
| virtual double | CalcOutput (const double input)=0 |
| The function that maps between the weighted sum that's the input of the neuron and the output. | |
| virtual double | CalcDeriv (const double input)=0 |
| The derivative of the function defined in CalcOutput. | |
| GeneralActivationFunction () | |
| virtual | ~GeneralActivationFunction () |
Detailed Description
The base class for all activation functions in neural network.The activation function in a neural network node determines the type of non-linearity between input and output. We have to implement the activation function and its derivative.
Definition at line 13 of file GeneralActivationFunction.h.
Constructor & Destructor Documentation
| GeneralActivationFunction::GeneralActivationFunction | ( | ) |
Definition at line 3 of file GeneralActivationFunction.cpp.
| GeneralActivationFunction::~GeneralActivationFunction | ( | ) | [virtual] |
Definition at line 5 of file GeneralActivationFunction.cpp.
Member Function Documentation
| virtual double GeneralActivationFunction::CalcOutput | ( | const double | input | ) | [pure virtual] |
The function that maps between the weighted sum that's the input of the neuron and the output.
Implemented in BipolarActivationFunction, and IdentityActivationFunction.
| virtual double GeneralActivationFunction::CalcDeriv | ( | const double | input | ) | [pure virtual] |
The derivative of the function defined in CalcOutput.
Implemented in BipolarActivationFunction, and IdentityActivationFunction.
The documentation for this class was generated from the following files:
