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
The derivative of the function defined in CalcOutput.
Implemented in BipolarActivationFunction, and IdentityActivationFunction.
The function that maps between the weighted sum that's the input of the neuron and the output.
Implemented in BipolarActivationFunction, and IdentityActivationFunction.
The documentation for this class was generated from the following files:
