24 #ifndef __ABSTRACTMODEL_H
25 #define __ABSTRACTMODEL_H
50 virtual void init(
unsigned int inputDim,
unsigned int outputDim,
51 double unit_map = 0.0,
RandGen* randGen = 0) = 0;
65 double learnRateFactor = 1) = 0;
68 virtual void damp(
double damping) = 0;
Matrix type.
Definition: matrix.h:65
Interface for objects, that can be stored and restored to/from a file stream (binary).
Definition: storeable.h:33
virtual unsigned int getInputDim() const =0
returns the number of input neurons
AbstractModel(const std::string &name, const std::string &revision)
Definition: abstractmodel.h:38
virtual const matrix::Matrix process(const matrix::Matrix &input)=0
passive processing of the input (this function is not constant since a recurrent network for example ...
virtual unsigned int getOutputDim() const =0
returns the number of output neurons
virtual void damp(double damping)=0
damps the weights and the biases by multiplying (1-damping)
random generator with 48bit integer arithmentic
Definition: randomgenerator.h:34
virtual const matrix::Matrix learn(const matrix::Matrix &input, const matrix::Matrix &nom_output, double learnRateFactor=1)=0
virtual void init(unsigned int inputDim, unsigned int outputDim, double unit_map=0.0, RandGen *randGen=0)=0
initialisation of the network with the given number of input and output units
Interface for inspectable objects.
Definition: inspectable.h:48
Abstact class for configurable objects.
Definition: configurable.h:81
abstract class (interface) for a model that can be used by a controller
Definition: abstractmodel.h:34
virtual ~AbstractModel()
Definition: abstractmodel.h:40