TarzaNN
TarzaNN neural network simulator
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Self Organizing map learning fp - Risto Miikkulainen, James A. Bednar, Yoonsuck Choe, and Joseph Sirosh. Computational Maps in the Visual Cortex. Springer, Berlin, 2005. More...
#include <SOMFeaturePlane.h>
Public Member Functions | |
~SOMFeaturePlane () | |
void | read (QDataStream *inStream, QProgressDialog *progress, int *index) |
void | save (QDataStream *outStream, QProgressDialog *progress, int *index) |
bool | isLearning () |
Protected Member Functions | |
SOMFeaturePlane (Network *net, int l, QString *name, int w, int h, int angles, int speeds, int alpha, int speed, bool isWTA, bool visible, Neuron *neuron, NotifyStrategyAbstract *notify, bool learning) | |
void | step () |
float | nonlinearity (Matrix *totalActivation, OutputImage *workOutput) |
Friends | |
class | GatingUnits |
class | FeaturePlaneFactory |
Self Organizing map learning fp - Risto Miikkulainen, James A. Bednar, Yoonsuck Choe, and Joseph Sirosh. Computational Maps in the Visual Cortex. Springer, Berlin, 2005.
SOMFeaturePlane::~SOMFeaturePlane | ( | ) |
SOMFeaturePlane::SOMFeaturePlane | ( | Network * | net, |
int | l, | ||
QString * | name, | ||
int | w, | ||
int | h, | ||
int | angles, | ||
int | speeds, | ||
int | alpha, | ||
int | speed, | ||
bool | isWTA, | ||
bool | visible, | ||
Neuron * | neuron, | ||
NotifyStrategyAbstract * | notify, | ||
bool | learning | ||
) | [protected] |
Constructor
net | - network, this FP will be added to the end of the list of feature planes |
l | - layer index |
name | - name of the feature plane |
w | - width |
h | - height |
angles | - number of discrete angles (e.g. speeds, orientations) |
speeds | - number of speeds (e.g. speed bands, scale bands) |
alpha | - alpha |
speed | - speed of this fp |
isWTA | - participates in Selective Tuning |
visible | - should the FP be presented in the UI |
neuron | - neuron strategy (what is the output nonlinearity, or the ODE that defines response) |
notify | - notification strategy (deprecated, on the way out) |
learning | - are weights adjustable through learning? |
bool SOMFeaturePlane::isLearning | ( | ) |
float SOMFeaturePlane::nonlinearity | ( | Matrix * | totalActivation, |
OutputImage * | workOutput | ||
) | [protected] |
void SOMFeaturePlane::read | ( | QDataStream * | inStream, |
QProgressDialog * | progress, | ||
int * | index | ||
) | [virtual] |
Implements LearningFeaturePlane.
void SOMFeaturePlane::save | ( | QDataStream * | outStream, |
QProgressDialog * | progress, | ||
int * | index | ||
) | [virtual] |
Implements LearningFeaturePlane.
void SOMFeaturePlane::step | ( | ) | [protected, virtual] |
Do one computation step - compute activations, and FP output
Reimplemented from FeaturePlane.
friend class FeaturePlaneFactory [friend] |
Reimplemented from LearningFeaturePlane.
friend class GatingUnits [friend] |
Reimplemented from LearningFeaturePlane.