#include <NeuralNetwork.h>

Inheritance diagram for gplib::NeuralNetwork:

Public Types
typedef std::vector < boost::shared_ptr < GeneralNeuron > >	tNeuralLayer

typedef std::vector< tNeuralLayer >	tNeuralArray

typedef std::vector < SigmoidalNeuron::tneurontype >	ttypeVector

typedef std::vector< ttypeVector >	ttypeArray

Public Member Functions
void	SetAlpha (const double a)
	Set the momentum multiplier. More...

void	SetMu (const double m)
	Set the adaptation stepsize. More...

void	SetLayers (ttypeArray typeArray, bool cachedoutput=false)
	Configure the layers of the network according to the types in typeArray. More...

void	InitWeights (const double MaxWeight, const double MaxBias)
	Initialize the weights with random values with the specified maxima. More...

void	PrintTopology (std::string filename)
	Print the topology and weights of the network for plotting with the dot program. More...

virtual void	PrintWeights (std::ostream &output)
	Print the weights of the network to the specified output stream. More...

virtual const gplib::rvec &	GetWeightsAsVector ()
	Return the network weights as a single vector. More...

virtual void	AdaptFilter (const gplib::rvec &Input, const gplib::rvec &Desired)
	Adapt the Filter with the current input and desired. More...

virtual void	CalcOutput (const gplib::rvec &Input, gplib::rvec &Output)
	Calculate the output with the given input. More...

	NeuralNetwork (const int inputsize, const int outputsize)
	The minium values for the network are the length of the input and output. More...

	NeuralNetwork (const int inputsize, const int outputsize, const double mu_, const ttypeArray &Layerssetup, const double maxinit, bool cachedoutput=false)
	Extended constructor with most of the necessary values. More...

virtual	~NeuralNetwork ()

Public Member Functions inherited from gplib::AdaptiveFilter
const gplib::rvec &	GetFilterOutput () const
	Access to the last calculated output (not sure if needed) More...

const gplib::rvec &	GetEpsilon () const
	Return the last estimation error. More...

	AdaptiveFilter (const int inputsize, const int outputsize)
	The constructor needs to know the length of the input and output vectors for memory allocation. More...

virtual	~AdaptiveFilter ()

Additional Inherited Members
Protected Member Functions inherited from gplib::AdaptiveFilter
unsigned int	GetInputLength ()
	Access function for derived classes for the inputlength. More...

unsigned int	GetOutputLength ()
	Access function for derived classes for the outputlength. More...

void	SetEpsilon (const gplib::rvec &MyEps)
	Possibility for derived classes to set estimation error. More...

void	SetOutput (const gplib::rvec &Out)
	Possibility for derived classes to set output. More...

Detailed Description

The class NeuralNetwork manages the network output calculation, neuron storage and weight adaptation Derived from AdaptiveFilter so we can use the Filter functionality

Definition at line 17 of file NeuralNetwork.h.

Member Typedef Documentation

typedef std::vector<tNeuralLayer> gplib::NeuralNetwork::tNeuralArray

Definition at line 21 of file NeuralNetwork.h.

typedef std::vector<boost::shared_ptr<GeneralNeuron> > gplib::NeuralNetwork::tNeuralLayer

Definition at line 20 of file NeuralNetwork.h.

typedef std::vector<ttypeVector> gplib::NeuralNetwork::ttypeArray

Definition at line 23 of file NeuralNetwork.h.

typedef std::vector<SigmoidalNeuron::tneurontype> gplib::NeuralNetwork::ttypeVector

Definition at line 22 of file NeuralNetwork.h.

Constructor & Destructor Documentation

gplib::NeuralNetwork::NeuralNetwork	(	const int	inputsize,
		const int	outputsize
	)

The minium values for the network are the length of the input and output.

Definition at line 13 of file NeuralNetwork.cpp.

gplib::NeuralNetwork::NeuralNetwork	(	const int	inputsize,
		const int	outputsize,
		const double	mu_,
		const ttypeArray &	Layerssetup,
		const double	maxinit,
		bool	cachedoutput = `false`
	)