gplib::NeuralNetwork Class Reference
[Neural Network filtering]
#include <NeuralNetwork.h>
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. | |
| void | SetMu (const double m) |
| Set the adaptation stepsize. | |
| void | SetLayers (ttypeArray typeArray, bool cachedoutput=false) |
| Configure the layers of the network according to the types in typeArray. | |
| void | InitWeights (const double MaxWeight, const double MaxBias) |
| Initialize the weights with random values with the specified maxima. | |
| void | PrintTopology (std::string filename) |
| Print the topology and weights of the network for plotting with the dot program. | |
| virtual void | PrintWeights (std::ostream &output) |
| Print the weights of the network to the specified output stream. | |
| virtual const gplib::rvec & | GetWeightsAsVector () |
| Return the network weights as a single vector. | |
| virtual void | AdaptFilter (const gplib::rvec &Input, const gplib::rvec &Desired) |
| Adapt the Filter with the current input and desired. | |
| virtual void | CalcOutput (const gplib::rvec &Input, gplib::rvec &Output) |
| Calculate the output with the given input. | |
| NeuralNetwork (const int inputsize, const int outputsize) | |
| The minium values for the network are the length of the input and output. | |
| 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. | |
| virtual | ~NeuralNetwork () |
Detailed Description
The class NeuralNetwork manages the network output calculation, neuron storage and weight adaptation Derived from AdaptiveFilter so we can use the Filter functionalityDefinition 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
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 | |||
| ) |
Extended constructor with most of the necessary values.
Definition at line 20 of file NeuralNetwork.cpp.
References InitWeights(), and SetLayers().
| gplib::NeuralNetwork::~NeuralNetwork | ( | ) | [virtual] |
Definition at line 31 of file NeuralNetwork.cpp.
Member Function Documentation
| void gplib::NeuralNetwork::AdaptFilter | ( | const gplib::rvec & | Input, | |
| const gplib::rvec & | Desired | |||
| ) | [virtual] |
Adapt the Filter with the current input and desired.
Implements gplib::AdaptiveFilter.
Definition at line 35 of file NeuralNetwork.cpp.
References gplib::AdaptiveFilter::GetFilterOutput(), and gplib::AdaptiveFilter::SetEpsilon().
Referenced by main().
| void gplib::NeuralNetwork::CalcOutput | ( | const gplib::rvec & | Input, | |
| gplib::rvec & | Output | |||
| ) | [virtual] |
Calculate the output with the given input.
Implements gplib::AdaptiveFilter.
Definition at line 45 of file NeuralNetwork.cpp.
References gplib::AdaptiveFilter::SetOutput().
| const gplib::rvec & gplib::NeuralNetwork::GetWeightsAsVector | ( | ) | [virtual] |
Return the network weights as a single vector.
Implements gplib::AdaptiveFilter.
Definition at line 58 of file NeuralNetwork.cpp.
References size.
Referenced by PrintTopology().
Initialize the weights with random values with the specified maxima.
Definition at line 122 of file NeuralNetwork.cpp.
References gplib::UniformRNG::GetNumber().
Referenced by main(), and NeuralNetwork().
| void gplib::NeuralNetwork::PrintTopology | ( | std::string | filename | ) |
Print the topology and weights of the network for plotting with the dot program.
Definition at line 233 of file NeuralNetwork.cpp.
References GetWeightsAsVector(), and size.
Referenced by main().
| void gplib::NeuralNetwork::PrintWeights | ( | std::ostream & | output | ) | [virtual] |
Print the weights of the network to the specified output stream.
Implements gplib::AdaptiveFilter.
Definition at line 219 of file NeuralNetwork.cpp.
Referenced by main().
| void gplib::NeuralNetwork::SetAlpha | ( | const double | a | ) | [inline] |
| void gplib::NeuralNetwork::SetLayers | ( | ttypeArray | typeArray, | |
| bool | cachedoutput = false | |||
| ) |
Configure the layers of the network according to the types in typeArray.
Definition at line 81 of file NeuralNetwork.cpp.
Referenced by main(), and NeuralNetwork().
| void gplib::NeuralNetwork::SetMu | ( | const double | m | ) | [inline] |
The documentation for this class was generated from the following files:
