Automatically generated with Code Structure Viewer (CS), Project Version: 3o4d 17-November-2020
Copyright © 2020, BAI Research. All Rights Reserved.
File Name: ANNformation.cpp/.hpp
File Description: ANN formation
name | return type | description |
---|---|---|
formNeuralNetworkInputLayer | void | form neural network input layer |
name | type | description |
---|---|---|
firstInputNeuronInNetwork | ANNneuron* | first input neuron in network |
numberOfInputNeurons | const int | number of input neurons |
location | current function being traced |
---|---|
ANNmain.hpp | formNeuralNetworkInputLayer |
name | return type | description |
---|---|---|
formNeuralNetWithOptimisedProperties | ANNneuron* | form neural net with optimised properties |
name | type | description |
---|---|---|
firstInputNeuronInNetwork | ANNneuron* | first input neuron in network |
numberOfInputNeurons | const int64_t | number of input neurons |
numberOfOutputNeurons | int64_t | number of output neurons |
numberOfLayers | const int64_t | number of layers |
location | current function being traced |
---|---|
ANNmain.hpp | formNeuralNetWithOptimisedProperties |
ANNmain.hpp | createNetwork |
ANNmain.hpp | mainUI |
name | return type | description |
---|---|---|
formNeuralNet | ANNneuron* | form neural net |
name | type | description |
---|---|---|
firstInputNeuron | ANNneuron* | first input neuron |
numberOfInputNeurons | const int64_t | number of input neurons |
numberOfOutputNeurons | int64_t | number of output neurons |
numberOfLayers | const int64_t | number of layers |
layerDivergenceType | const int | layer divergence type |
meanLayerDivergenceFactor | const double | mean layer divergence factor |
probabilityANNneuronConnectionWithPreviousLayerNeuron | const double | probability ANN neuron connection with previous layer neuron |
probabilityANNneuronConnectionWithAllPreviousLayersNeurons | const double | probability ANN neuron connection with all previous layers neurons |
location | current function being traced |
---|---|
ANNformation.hpp | formNeuralNet |
ANNmain.hpp | formNeuralNetWithOptimisedProperties |
ANNmain.hpp | createNetwork |
ANNmain.hpp | mainUI |
name | return type | description |
---|---|---|
formAdvancedNeuralNetwork | ANNneuron* | form advanced neural network |
name | type | description |
---|---|---|
firstInputNeuron | ANNneuron* | first input neuron |
numberOfInputNeurons | const int64_t | number of input neurons |
numberOfOutputNeurons | int64_t | number of output neurons |
useSubnetDependentNumberOfLayers | const bool | use subnet dependent number of layers |
probabilityOfSubnetCreation | const double | probability of subnet creation |
maxNumberOfRecursiveSubnets | const int64_t | max number of recursive subnets |
numberOfLayers | const int64_t | number of layers |
layerDivergenceType | const int | layer divergence type |
meanLayerDivergenceFactor | const double | mean layer divergence factor |
probabilityANNneuronConnectionWithPreviousLayerNeuron | const double | probability ANN neuron connection with previous layer neuron |
probabilityANNneuronConnectionWithAllPreviousLayersNeurons | const double | probability ANN neuron connection with all previous layers neurons |
location | current function being traced |
---|---|
ANNmain.hpp | formAdvancedNeuralNetwork |
ANNmain.hpp | createNetwork |
ANNmain.hpp | mainUI |
name | return type | description |
---|---|---|
formNonDistinctLayeredNeuralNetwork | ANNneuron* | form non distinct layered neural network |
name | type | description |
---|---|---|
firstInputNeuronInNetwork | ANNneuron* | first input neuron in network |
numberOfInputNeurons | const int64_t | number of input neurons |
numberOfOutputNeurons | int64_t | number of output neurons |
numberOfLayers | const int64_t | number of layers |
probabilityOfSubnetCreation | const double | probability of subnet creation |
maxNumberOfRecursiveSubnets | const int64_t | max number of recursive subnets |
useSubnetDependentNumberOfLayers | const bool | use subnet dependent number of layers |
subnetNumberOfLayersModifier | const double | subnet number of layers modifier |
layerDivergenceType | const int | layer divergence type |
meanLayerDivergenceFactor | const double | mean layer divergence factor |
probabilityANNneuronConnectionWithPreviousLayerNeuron | const double | probability ANN neuron connection with previous layer neuron |
probabilityANNneuronConnectionWithAllPreviousLayersNeurons | const double | probability ANN neuron connection with all previous layers neurons |
location | current function being traced |
---|---|
ANNformation.hpp | formNonDistinctLayeredNeuralNetwork |
ANNformation.hpp | formNeuralNet |
ANNmain.hpp | formNeuralNetWithOptimisedProperties |
ANNmain.hpp | createNetwork |
ANNmain.hpp | mainUI |
ANNformation.hpp | formNonDistinctLayeredNeuralNetwork |
name | return type | description |
---|---|---|
createInputLayerInNeuralNetwork | void | create input layer in neural network |
name | type | description |
---|---|---|
firstInputNeuronInNetwork | ANNneuron* | first input neuron in network |
numberOfInputNeurons | const int64_t | number of input neurons |
location | current function being traced |
---|---|
ANNformation.hpp | createInputLayerInNeuralNetwork |
ANNformation.hpp | formNonDistinctLayeredNeuralNetwork |
ANNformation.hpp | formNeuralNet |
ANNmain.hpp | formNeuralNetWithOptimisedProperties |
ANNmain.hpp | createNetwork |
ANNmain.hpp | mainUI |
ANNformation.hpp | formNonDistinctLayeredNeuralNetwork |
name | return type | description |
---|---|---|
createInputLayerInNeuralNetwork2D | void | create input layer in neural network 2D |
name | type | description |
---|---|---|
firstInputNeuronInNetwork | ANNneuron* | first input neuron in network |
numberOfInputNeurons | const int64_t | number of input neurons |
location | current function being traced |
---|---|
ANNformation.hpp | createInputLayerInNeuralNetwork2D |
ANNformation.hpp | formNonDistinctLayeredNeuralNetwork |
ANNformation.hpp | formNeuralNet |
ANNmain.hpp | formNeuralNetWithOptimisedProperties |
ANNmain.hpp | createNetwork |
ANNmain.hpp | mainUI |
ANNformation.hpp | formNonDistinctLayeredNeuralNetwork |
name | return type | description |
---|---|---|
fillNonDistinctHiddenLayer | ANNneuron* | fill non distinct hidden layer |
name | type | description |
---|---|---|
firstNeuronInCurrentLayer | ANNneuron* | first neuron in current layer |
numberOfInputNeurons | const int64_t | number of input neurons |
numberOfOutputNeurons | int64_t | number of output neurons |
numberOfNeuronsInCurrentLayer | const int64_t | number of neurons in current layer |
currentNumberOfLayers | const int64_t | current number of layers |
numberOfLayers | const int64_t | number of layers |
probabilityOfSubnetCreation | const double | probability of subnet creation |
maxNumberOfRecursiveSubnets | const int64_t | max number of recursive subnets |
currentNumberOfRecursiveSubnets | const int64_t | current number of recursive subnets |
useSubnetDependentNumberOfLayers | const bool | use subnet dependent number of layers |
subnetNumberOfLayersModifier | const double | subnet number of layers modifier |
layerDivergenceType | const int | layer divergence type |
meanLayerDivergenceFactor | const double | mean layer divergence factor |
probabilityANNneuronConnectionWithPreviousLayerNeuron | const double | probability ANN neuron connection with previous layer neuron |
firstInputNeuronInSubnet | ANNneuron* | first input neuron in subnet |
probabilityANNneuronConnectionWithAllPreviousLayersNeurons | const double | probability ANN neuron connection with all previous layers neurons |
onlyLinkWithPreviousAndFirstLayer | const bool | only link with previous and first layer |
location | current function being traced |
---|---|
ANNformation.hpp | fillNonDistinctHiddenLayer |
ANNformation.hpp | formNonDistinctLayeredNeuralNetwork |
ANNformation.hpp | formNeuralNet |
ANNmain.hpp | formNeuralNetWithOptimisedProperties |
ANNmain.hpp | createNetwork |
ANNmain.hpp | mainUI |
ANNformation.hpp | formNonDistinctLayeredNeuralNetwork |
ANNalgorithmBreakawayNetwork.hpp | fillNonDistinctHiddenLayer |
ANNmain.hpp | trainNeuralNetworkBreakaway |
name | return type | description |
---|---|---|
createNewFrontLayer | void | create new front layer |
name | type | description |
---|---|---|
firstNeuronInCurrentLayer | ANNneuron* | first neuron in current layer |
firstNeuronInNewFrontLayer | ANNneuron* | first neuron in new front layer |
numberOfNeuronsInNewFrontLayer | const int64_t | number of neurons in new front layer |
currentNumberOfLayers | const int64_t | current number of layers |
numberOfLayers | const int64_t | number of layers |
location | current function being traced |
---|---|
ANNformation.hpp | createNewFrontLayer |
ANNformation.hpp | fillNonDistinctHiddenLayer |
ANNformation.hpp | formNonDistinctLayeredNeuralNetwork |
ANNformation.hpp | formNeuralNet |
ANNmain.hpp | formNeuralNetWithOptimisedProperties |
ANNmain.hpp | createNetwork |
ANNmain.hpp | mainUI |
ANNformation.hpp | formNonDistinctLayeredNeuralNetwork |
ANNalgorithmBreakawayNetwork.hpp | fillNonDistinctHiddenLayer |
ANNmain.hpp | trainNeuralNetworkBreakaway |
name | return type | description |
---|---|---|
linkNewFrontLayerWithPreviousLayers | void | link new front layer with previous layers |
name | type | description |
---|---|---|
firstNeuronInCurrentLayer | ANNneuron* | first neuron in current layer |
firstNeuronInNewFrontLayer | ANNneuron* | first neuron in new front layer |
probabilityANNneuronConnectionWithPreviousLayerNeuron | const double | probability ANN neuron connection with previous layer neuron |
firstInputNeuronInSubnet | ANNneuron* | first input neuron in subnet |
probabilityANNneuronConnectionWithAllPreviousLayersNeurons | const double | probability ANN neuron connection with all previous layers neurons |
numberOfInputNeurons | const int64_t | number of input neurons |
numberOfOutputNeurons | const int64_t | number of output neurons |
currentNumberOfLayers | const int64_t | current number of layers |
onlyLinkWithPreviousAndFirstLayer | const bool | only link with previous and first layer |
location | current function being traced |
---|---|
ANNformation.hpp | linkNewFrontLayerWithPreviousLayers |
ANNformation.hpp | fillNonDistinctHiddenLayer |
ANNformation.hpp | formNonDistinctLayeredNeuralNetwork |
ANNformation.hpp | formNeuralNet |
ANNmain.hpp | formNeuralNetWithOptimisedProperties |
ANNmain.hpp | createNetwork |
ANNmain.hpp | mainUI |
ANNformation.hpp | formNonDistinctLayeredNeuralNetwork |
ANNalgorithmBreakawayNetwork.hpp | fillNonDistinctHiddenLayer |
ANNmain.hpp | trainNeuralNetworkBreakaway |
name | return type | description |
---|---|---|
linkNewFrontLayerWithPreviousLayers2D | void | link new front layer with previous layers 2D |
name | type | description |
---|---|---|
firstNeuronInCurrentLayer | ANNneuron* | first neuron in current layer |
firstNeuronInNewFrontLayer | ANNneuron* | first neuron in new front layer |
probabilityANNneuronConnectionWithPreviousLayerNeuron | const double | probability ANN neuron connection with previous layer neuron |
firstInputNeuronInSubnet | ANNneuron* | first input neuron in subnet |
probabilityANNneuronConnectionWithAllPreviousLayersNeurons | const double | probability ANN neuron connection with all previous layers neurons |
numberOfInputNeurons | const int64_t | number of input neurons |
numberOfOutputNeurons | const int64_t | number of output neurons |
currentNumberOfLayers | const int64_t | current number of layers |
numberOfLayers | const int64_t | number of layers |
numberOfNeuronsInCurrentLayer | const int64_t | number of neurons in current layer |
numberOfNeuronsInNewFrontLayer | const int64_t | number of neurons in new front layer |
layerDivergenceType | const int | layer divergence type |
onlyLinkWithPreviousAndFirstLayer | const bool | only link with previous and first layer |
location | current function being traced |
---|---|
ANNformation.hpp | linkNewFrontLayerWithPreviousLayers2D |
ANNformation.hpp | fillNonDistinctHiddenLayer |
ANNformation.hpp | formNonDistinctLayeredNeuralNetwork |
ANNformation.hpp | formNeuralNet |
ANNmain.hpp | formNeuralNetWithOptimisedProperties |
ANNmain.hpp | createNetwork |
ANNmain.hpp | mainUI |
ANNformation.hpp | formNonDistinctLayeredNeuralNetwork |
ANNalgorithmBreakawayNetwork.hpp | fillNonDistinctHiddenLayer |
ANNmain.hpp | trainNeuralNetworkBreakaway |
name | return type | description |
---|---|---|
calcNumberOfLayersInSubnet | int64_t | calc number of layers in subnet |
name | type | description |
---|---|---|
numberOfInputNeurons | const int64_t | number of input neurons |
numberOfOutputNeurons | const int64_t | number of output neurons |
currentNumberOfRecursiveSubnets | const int64_t | current number of recursive subnets |
maxNumberOfRecursiveSubnets | const int64_t | max number of recursive subnets |
useSubnetDependentNumberOfLayers | const bool | use subnet dependent number of layers |
subnetNumberOfLayersModifier | const double | subnet number of layers modifier |
location | current function being traced |
---|---|
ANNformation.hpp | calcNumberOfLayersInSubnet |
ANNformation.hpp | fillNonDistinctHiddenLayer |
ANNformation.hpp | formNonDistinctLayeredNeuralNetwork |
ANNformation.hpp | formNeuralNet |
ANNmain.hpp | formNeuralNetWithOptimisedProperties |
ANNmain.hpp | createNetwork |
ANNmain.hpp | mainUI |
ANNformation.hpp | formNonDistinctLayeredNeuralNetwork |
ANNalgorithmBreakawayNetwork.hpp | fillNonDistinctHiddenLayer |
ANNmain.hpp | trainNeuralNetworkBreakaway |
name | return type | description |
---|---|---|
advancedDivergenceFactor | double | advanced divergence factor |
name | type | description |
---|---|---|
currentNumberOfLayersFromNearestEndPoint | const int64_t | current number of layers from nearest end point |
numberOfLayers | const int64_t | number of layers |
location | current function being traced |
---|---|
ANNformation.hpp | advancedDivergenceFactor |
ANNformation.hpp | calculateNumberOfNeuronsInNewFrontLayer |
ANNformation.hpp | fillNonDistinctHiddenLayer |
ANNformation.hpp | formNonDistinctLayeredNeuralNetwork |
ANNformation.hpp | formNeuralNet |
ANNmain.hpp | formNeuralNetWithOptimisedProperties |
ANNmain.hpp | createNetwork |
ANNmain.hpp | mainUI |
ANNformation.hpp | formNonDistinctLayeredNeuralNetwork |
ANNalgorithmBreakawayNetwork.hpp | fillNonDistinctHiddenLayer |
ANNmain.hpp | trainNeuralNetworkBreakaway |
name | return type | description |
---|---|---|
calculateNumberOfNeuronsInNewFrontLayer | int64_t | calculate number of neurons in new front layer |
name | type | description |
---|---|---|
numberOfInputNeurons | const int64_t | number of input neurons |
numberOfOutputNeurons | int64_t | number of output neurons |
numberOfNeuronsInCurrentLayer | const int64_t | number of neurons in current layer |
currentNumberOfLayers | const int64_t | current number of layers |
numberOfLayers | const int64_t | number of layers |
meanLayerDivergenceFactor | const double | mean layer divergence factor |
layerDivergenceType | const int | layer divergence type |
location | current function being traced |
---|---|
ANNformation.hpp | calculateNumberOfNeuronsInNewFrontLayer |
ANNformation.hpp | fillNonDistinctHiddenLayer |
ANNformation.hpp | formNonDistinctLayeredNeuralNetwork |
ANNformation.hpp | formNeuralNet |
ANNmain.hpp | formNeuralNetWithOptimisedProperties |
ANNmain.hpp | createNetwork |
ANNmain.hpp | mainUI |
ANNformation.hpp | formNonDistinctLayeredNeuralNetwork |
ANNalgorithmBreakawayNetwork.hpp | fillNonDistinctHiddenLayer |
ANNmain.hpp | trainNeuralNetworkBreakaway |
name | return type | description |
---|---|---|
calculateDistanceBetween2Points | double | calculate distance between 2P oints |
name | type | description |
---|---|---|
xPositionOfUnit1 | const double | xPosition of unit 1 |
xPositionOfUnit2 | const double | xPosition of unit 2 |
yPositionOfUnit1 | const double | yPosition of unit 1 |
yPositionOfUnit2 | const double | yPosition of unit 2 |
location | current function being traced |
---|---|
ANNformation.hpp | calculateDistanceBetween2Points |
ANNformation.hpp | linkNewFrontLayerWithPreviousLayers2D |
ANNformation.hpp | fillNonDistinctHiddenLayer |
ANNformation.hpp | formNonDistinctLayeredNeuralNetwork |
ANNformation.hpp | formNeuralNet |
ANNmain.hpp | formNeuralNetWithOptimisedProperties |
ANNmain.hpp | createNetwork |
ANNmain.hpp | mainUI |
ANNformation.hpp | formNonDistinctLayeredNeuralNetwork |
ANNalgorithmBreakawayNetwork.hpp | fillNonDistinctHiddenLayer |
ANNmain.hpp | trainNeuralNetworkBreakaway |
ANNformation.hpp | calculateDistanceBetween2Points |
name | return type | description |
---|---|---|
addSideConnectionsForLayer | void | add side connections for layer |
name | type | description |
---|---|---|
firstNeuronInLayer | ANNneuron* | first neuron in layer |
location | current function being traced |
---|---|
ANNformation.hpp | addSideConnectionsForLayer |
ANNformation.hpp | linkNewFrontLayerWithPreviousLayers |
ANNformation.hpp | fillNonDistinctHiddenLayer |
ANNformation.hpp | formNonDistinctLayeredNeuralNetwork |
ANNformation.hpp | formNeuralNet |
ANNmain.hpp | formNeuralNetWithOptimisedProperties |
ANNmain.hpp | createNetwork |
ANNmain.hpp | mainUI |
ANNformation.hpp | formNonDistinctLayeredNeuralNetwork |
ANNalgorithmBreakawayNetwork.hpp | fillNonDistinctHiddenLayer |
ANNmain.hpp | trainNeuralNetworkBreakaway |
name | return type | description |
---|---|---|
addSideConnectionsForLayer2D | void | add side connections for layer 2D |
name | type | description |
---|---|---|
firstNeuronInLayer | ANNneuron* | first neuron in layer |
layerDivergenceType | const int | layer divergence type |
currentNumberOfLayers | const int64_t | current number of layers |
numberOfLayers | const int64_t | number of layers |
location | current function being traced |
---|---|
ANNformation.hpp | addSideConnectionsForLayer2D |
ANNformation.hpp | linkNewFrontLayerWithPreviousLayers2D |
ANNformation.hpp | fillNonDistinctHiddenLayer |
ANNformation.hpp | formNonDistinctLayeredNeuralNetwork |
ANNformation.hpp | formNeuralNet |
ANNmain.hpp | formNeuralNetWithOptimisedProperties |
ANNmain.hpp | createNetwork |
ANNmain.hpp | mainUI |
ANNformation.hpp | formNonDistinctLayeredNeuralNetwork |
ANNalgorithmBreakawayNetwork.hpp | fillNonDistinctHiddenLayer |
ANNmain.hpp | trainNeuralNetworkBreakaway |
name | return type | description |
---|---|---|
addSideConnectionIfNotAlreadyAdded | void | add side connection if not already added |
name | type | description |
---|---|---|
currentNeuronL1 | ANNneuron* | current neuron L1 |
currentNeuronL2 | ANNneuron* | current neuron L2 |
location | current function being traced |
---|---|
ANNformation.hpp | addSideConnectionIfNotAlreadyAdded |
ANNformation.hpp | addSideConnectionsForLayer |
ANNformation.hpp | linkNewFrontLayerWithPreviousLayers |
ANNformation.hpp | fillNonDistinctHiddenLayer |
ANNformation.hpp | formNonDistinctLayeredNeuralNetwork |
ANNformation.hpp | formNeuralNet |
ANNmain.hpp | formNeuralNetWithOptimisedProperties |
ANNmain.hpp | createNetwork |
ANNmain.hpp | mainUI |
ANNformation.hpp | formNonDistinctLayeredNeuralNetwork |
ANNalgorithmBreakawayNetwork.hpp | fillNonDistinctHiddenLayer |
ANNmain.hpp | trainNeuralNetworkBreakaway |
ANNformation.hpp | addSideConnectionIfNotAlreadyAdded |
ANNformation.hpp | addSideConnectionsForLayer2D |
name | return type | description |
---|---|---|
countNumberOfLayersInSubnet | int | count number of layers in subnet |
name | type | description |
---|---|---|
firstInputNeuronInSubnet | ANNneuron* | first input neuron in subnet |
location | current function being traced |
---|---|
ANNmain.hpp | countNumberOfLayersInSubnet |
ANNmain.hpp | trainNetwork |
ANNmain.hpp | mainUI |