SimpleNeuron Class Reference

A simple perceptron - i.e., it takes as input the weighted sum of the outputs of the neurons connected to it. More...

#include <SimpleNeuron.h>

Inheritance diagram for SimpleNeuron:

[legend]Collaboration diagram for SimpleNeuron:

[legend]List of all members.

Public Member Functions
	SimpleNeuron (int label, bool hasBias=true)
	Creates a simple neuron with the given label.
virtual void	setDesiredOutput (real desired)
	Sets the desired output of the neuron.
virtual void	setActivationFunction (ActivationFunction f, ActivationFunction df)
	Sets the activation function and its derivative (required for error backpropagation).
virtual const char *	getClassName () const
	Returns "SimpleNeuron".
Protected Member Functions
virtual void	_recacheOutput () const
	Neuron::_recacheOutput.
virtual void	_recacheError () const
	Neuron::_recacheError.
Protected Attributes
ActivationFunction	_dActivationFunction
	The derivative of the activation function, required for gradient descent training.

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Detailed Description

A simple perceptron - i.e., it takes as input the weighted sum of the outputs of the neurons connected to it.

Probably the first type of neuron you would come across in any introductory literature of neural networks.

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Constructor & Destructor Documentation

SimpleNeuron (  int  label, bool  hasBias = true )

Creates a simple neuron with the given label. Parameters: label  The label to be given to the neuron hasBias  true if the neuron is allowed to have a bias, false otherwise. Default is true See also: removeBias

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Member Function Documentation

virtual void _recacheError (   )  const [protected, virtual]

Neuron::_recacheError. Implements AbstractNeuron.

virtual void _recacheOutput (   )  const [protected, virtual]

Neuron::_recacheOutput. Implements AbstractNeuron. Reimplemented in KohonenNeuron.

virtual const char* getClassName (   )  const [virtual]

Returns "SimpleNeuron". Reimplemented from AbstractNeuron. Reimplemented in RecurrentNeuron.

virtual void setActivationFunction (  ActivationFunction  f, ActivationFunction  df )  [virtual]

Sets the activation function and its derivative (required for error backpropagation). Parameters: f  The activation function to be used df  The derivative of the activation function

virtual void setDesiredOutput (  real  desired  )  [virtual]

Sets the desired output of the neuron. Should be called only for output neurons, i.e., those whose output is not connected to anyone else. Setting the desired output at these neurons will form the basis of error backpropagation Parameters: desired  The desired output of this neuron Exceptions: Exception  if the neuron is not an output neuron Implements AbstractNeuron.

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Member Data Documentation

ActivationFunction _dActivationFunction [protected]

The derivative of the activation function, required for gradient descent training.

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The documentation for this class was generated from the following file:

• SimpleNeuron.h

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