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A
- AI.NeuralNetworks - package AI.NeuralNetworks
- activation - Variable in class AI.NeuralNetworks.FeedForwardLayer
- addDeltaWeights() - Method in class AI.NeuralNetworks.BackErrorPropagation
- Adds the deltaWeights to the weights
- addDeltaWeights() - Method in class AI.NeuralNetworks.DistributedBackErrorPropagation
- Adds the all deltaWeights to the weights
- addDeltaWeights(float) - Method in class AI.NeuralNetworks.FeedForwardWeightedTrainingLayer
- Adds the deltaWeights to the weights
- addIntToArray(int[], int, int) - Static method in class AI.NeuralNetworks.FeedForwardNetwork
- adjustDeltaWeights(float[], float[]) - Method in class AI.NeuralNetworks.BackErrorPropagation
- Calculates the delta weights for this pattern and adds it to the acumlated deltas
- adjustDeltaWeights(float[], FeedForwardLayer) - Method in class AI.NeuralNetworks.FeedForwardWeightedTrainingLayer
- Calculates and adds the delta weights for this pattern
- adjustDeltaWeights(FeedForwardLayer, FeedForwardWeightedTrainingLayer) - Method in class AI.NeuralNetworks.FeedForwardWeightedTrainingLayer
- Calculates and adds the delta weights for this pattern
B
- BackErrorPropagation - class AI.NeuralNetworks.BackErrorPropagation.
- This Class is a nerual network with a multiple layer feed forward architecture where the back error propagation could be run
- BackErrorPropagation(FeedForwardNetwork, float, float, long, float) - Constructor for class AI.NeuralNetworks.BackErrorPropagation
- Creates a new BackErrorPropagation instance
- BackErrorPropagation(FeedForwardNetwork) - Constructor for class AI.NeuralNetworks.BackErrorPropagation
- Creates a new BackErrorPropagation instance
- BackErrorPropagation() - Constructor for class AI.NeuralNetworks.BackErrorPropagation
- this construcctor should not be used it is here for inheriterence only
- bw - Variable in class AI.NeuralNetworks.DistributedBackErrorPropagation
C
- COMMENT_TOKEN - Static variable in class AI.NeuralNetworks.BackErrorPropagation
- COMMENT_TOKEN - Static variable in class AI.NeuralNetworks.FeedForwardNetwork
- createWeights(BufferedReader, int, int) - Static method in class AI.NeuralNetworks.FeedForwardNetwork
D
- DEFAULT_LEARNING_RATE - Static variable in class AI.NeuralNetworks.BackErrorPropagation
- DEFAULT_MAXIMUM_EPOCH - Static variable in class AI.NeuralNetworks.BackErrorPropagation
- DEFAULT_MOMENTUM_RATE - Static variable in class AI.NeuralNetworks.BackErrorPropagation
- DEFAULT_STOP_ERROR - Static variable in class AI.NeuralNetworks.BackErrorPropagation
- DistributedBackErrorPropagation - class AI.NeuralNetworks.DistributedBackErrorPropagation.
- This Class is a nerual network with a multiple layer feed forward architecture where a distributed version of the back error propagation algorithm could be run
- DistributedBackErrorPropagation(FeedForwardNetwork, BufferedWriter) - Constructor for class AI.NeuralNetworks.DistributedBackErrorPropagation
- Creates a new DistributedBackErrorPropagation instance
- DistributedBackErrorPropagation(FeedForwardNetwork) - Constructor for class AI.NeuralNetworks.DistributedBackErrorPropagation
- Creates a new DistributedBackErrorPropagation instance
- DistributedFeedForwardWeightedTrainingLayer - class AI.NeuralNetworks.DistributedFeedForwardWeightedTrainingLayer.
- This class is used to represent the inner and output layers of a multilayer feed forward neural network
- DistributedFeedForwardWeightedTrainingLayer(FeedForwardWeightedLayer) - Constructor for class AI.NeuralNetworks.DistributedFeedForwardWeightedTrainingLayer
- creates a new insatnce of FeedForwardWeightedLayer
- deltaWeights - Variable in class AI.NeuralNetworks.FeedForwardWeightedTrainingLayer
E
- END_TOKEN - Static variable in class AI.NeuralNetworks.BackErrorPropagation
- error - Variable in class AI.NeuralNetworks.FeedForwardWeightedTrainingLayer
F
- FeedForwardInputLayer - class AI.NeuralNetworks.FeedForwardInputLayer.
- This class is used to represent the first layer of a multilayer feed forward neural network
- FeedForwardInputLayer(int) - Constructor for class AI.NeuralNetworks.FeedForwardInputLayer
- creates a new insatnce of FeedForwardInputLayer
- FeedForwardInputLayer(FeedForwardInputLayer) - Constructor for class AI.NeuralNetworks.FeedForwardInputLayer
- creates a new insatnce of FeedForwardInputLayer
- FeedForwardLayer - class AI.NeuralNetworks.FeedForwardLayer.
- A multilayer feed forewar nerual network is composed by layers those layers are subclases of this class.
- FeedForwardLayer() - Constructor for class AI.NeuralNetworks.FeedForwardLayer
- FeedForwardNetwork - class AI.NeuralNetworks.FeedForwardNetwork.
- This Class is a nerual network with a multiple layer feed forward architecture
- FeedForwardNetwork() - Constructor for class AI.NeuralNetworks.FeedForwardNetwork
- Creates a new FeedForwardNetwork This constructor should be only used by sublcases
- FeedForwardNetwork(int[]) - Constructor for class AI.NeuralNetworks.FeedForwardNetwork
- Creates a new FeedForwardNetwork
- FeedForwardNetwork(String) - Constructor for class AI.NeuralNetworks.FeedForwardNetwork
- Creates a new FeedForwardNetwork form the specified file
- FeedForwardNetwork(BufferedReader) - Constructor for class AI.NeuralNetworks.FeedForwardNetwork
- Creates a new FeedForwardNetwork form the specified BufferedReader
- FeedForwardNetwork(int[], int) - Constructor for class AI.NeuralNetworks.FeedForwardNetwork
- Creates a new FeedForwardNetwork form the specified BufferedReader
- FeedForwardWeightedLayer - class AI.NeuralNetworks.FeedForwardWeightedLayer.
- This class is used to represent the inner and output layers of a multilayer feed forward neural network
- FeedForwardWeightedLayer(int, int) - Constructor for class AI.NeuralNetworks.FeedForwardWeightedLayer
- creates a new insatnce of FeedForwardWeightedLayer
- FeedForwardWeightedLayer(FeedForwardWeightedLayer) - Constructor for class AI.NeuralNetworks.FeedForwardWeightedLayer
- creates a new insatnce of FeedForwardWeightedLayer
- FeedForwardWeightedLayer(float[][]) - Constructor for class AI.NeuralNetworks.FeedForwardWeightedLayer
- creates a new insatnce of FeedForwardWeightedLayer
- FeedForwardWeightedTrainingLayer - class AI.NeuralNetworks.FeedForwardWeightedTrainingLayer.
- This class is used to represent the inner and output layers of a multilayer feed forward neural network where the back error propabation algorithm is run
- FeedForwardWeightedTrainingLayer(FeedForwardWeightedLayer) - Constructor for class AI.NeuralNetworks.FeedForwardWeightedTrainingLayer
- Creates a new FeedForwardWeightedTrainingLayer instance form a FeedForwardWeightedLayer instance
G
- getActivation() - Method in class AI.NeuralNetworks.FeedForwardLayer
- Returns this layers activation
- getError() - Method in class AI.NeuralNetworks.FeedForwardWeightedTrainingLayer
- returns the error of the layer
- getNextStringTokenizer(BufferedReader, String) - Static method in class AI.NeuralNetworks.BackErrorPropagation
- getNextStringTokenizer(BufferedReader, String) - Static method in class AI.NeuralNetworks.FeedForwardNetwork
- getOutputError() - Method in class AI.NeuralNetworks.FeedForwardWeightedTrainingLayer
- getVectors(BufferedReader) - Static method in class AI.NeuralNetworks.BackErrorPropagation
- getVectorsFormFile(String) - Static method in class AI.NeuralNetworks.BackErrorPropagation
- getWeights() - Method in class AI.NeuralNetworks.FeedForwardWeightedLayer
H
- HEXADECIMAL_VERSION - Static variable in class AI.NeuralNetworks.FeedForwardNetwork
- hosts - Variable in class AI.NeuralNetworks.DistributedBackErrorPropagation
I
- INPUT_LAYER_TOKEN - Static variable in class AI.NeuralNetworks.FeedForwardNetwork
- INPUT_TOKEN - Static variable in class AI.NeuralNetworks.BackErrorPropagation
- input - Variable in class AI.NeuralNetworks.PatternPair
- input() - Method in class AI.NeuralNetworks.PatternPair
- Returns the input pattern
- inputSize() - Method in class AI.NeuralNetworks.FeedForwardNetwork
- returns the number of inputs of the net without counting the bias
L
- layers - Variable in class AI.NeuralNetworks.FeedForwardNetwork
- learningRate - Variable in class AI.NeuralNetworks.BackErrorPropagation
M
- maximumEpoch - Variable in class AI.NeuralNetworks.BackErrorPropagation
- momentumRate - Variable in class AI.NeuralNetworks.BackErrorPropagation
N
- NUMBER_OF_LAYERS_TOKEN - Static variable in class AI.NeuralNetworks.FeedForwardNetwork
- NeuralNetworkTeacher - interface AI.NeuralNetworks.NeuralNetworkTeacher.
- This interface defines a NerualNetwork Teacher
- Notify - interface AI.NeuralNetworks.Notify.
- This interface defines an Notify object.
- netToIntArrey() - Method in class AI.NeuralNetworks.FeedForwardNetwork
- returns a int[] which represents a netework the weightValues are converted to int with the Float.floatToIntBits() method.
- niceArray(float[]) - Static method in class AI.NeuralNetworks.DistributedBackErrorPropagation
- niceArray(int[]) - Static method in class AI.NeuralNetworks.DistributedBackErrorPropagation
- niceArray(float[]) - Static method in class AI.NeuralNetworks.PatternPair
- notify(Object) - Method in interface AI.NeuralNetworks.Notify
- this is the method called when is needed to notify
- notifyError - Variable in class AI.NeuralNetworks.BackErrorPropagation
O
- OUTPUT_TOKEN - Static variable in class AI.NeuralNetworks.BackErrorPropagation
- output - Variable in class AI.NeuralNetworks.PatternPair
- output() - Method in class AI.NeuralNetworks.PatternPair
- Returns the output pattern
- outputError - Variable in class AI.NeuralNetworks.FeedForwardWeightedTrainingLayer
- outputSize() - Method in class AI.NeuralNetworks.FeedForwardNetwork
- returns the number of outputs of the net without counting the bias
P
- PatternPair - class AI.NeuralNetworks.PatternPair.
- This class has a input - output pattern for a nerual netwrok
- PatternPair(float[], float[]) - Constructor for class AI.NeuralNetworks.PatternPair
- Creates a new PatternPair instnce
- parseDeltaWeights(BufferedReader) - Method in class AI.NeuralNetworks.DistributedBackErrorPropagation
- adds the delta weights form br to the local delta weights
- parseDeltaWeights(BufferedReader) - Method in class AI.NeuralNetworks.DistributedFeedForwardWeightedTrainingLayer
- adds the delta weights form br to the local delta weights
- parseStructure(String) - Static method in class AI.NeuralNetworks.BackErrorPropagation
- converts a string composed by tokens that could be converted to int to an array of int
R
- resetDeltaWeights() - Method in class AI.NeuralNetworks.BackErrorPropagation
- Sets the acumulated delta weights to 0
- resetDeltaWeights() - Method in class AI.NeuralNetworks.FeedForwardWeightedTrainingLayer
- Sets the acumulated delta weights to 0
- resetError() - Method in class AI.NeuralNetworks.FeedForwardWeightedTrainingLayer
- Sets the error of all this layer to 0
- runLayer(FeedForwardLayer) - Method in class AI.NeuralNetworks.FeedForwardWeightedLayer
- Calculates the new activation values of this layer based on the previous layer
- runVector(float[]) - Method in class AI.NeuralNetworks.FeedForwardNetwork
- Runs the network with the inputVector and returns the outputVector
S
- SEED_WIDTH - Static variable in class AI.NeuralNetworks.FeedForwardWeightedLayer
- save(BufferedWriter) - Method in class AI.NeuralNetworks.FeedForwardNetwork
- Saves the neural network
- saveToFile(String) - Method in class AI.NeuralNetworks.FeedForwardNetwork
- Saves the neural network
- sendDeltaWeights() - Method in class AI.NeuralNetworks.DistributedBackErrorPropagation
- sendDeltaWeights(BufferedWriter) - Method in class AI.NeuralNetworks.DistributedFeedForwardWeightedTrainingLayer
- Sendsthe deltaWeights to the weights in the BufferedWriter
- sendError(float) - Method in class AI.NeuralNetworks.DistributedBackErrorPropagation
- setInput(float[]) - Method in class AI.NeuralNetworks.FeedForwardInputLayer
- sets the input values of the layer
- setLearnningRate(float) - Method in class AI.NeuralNetworks.BackErrorPropagation
- Sets the learnning rate
- setMaximumEpoch(int) - Method in class AI.NeuralNetworks.BackErrorPropagation
- Sets the maximum epoch
- setNotifyError(Notify) - Method in class AI.NeuralNetworks.BackErrorPropagation
- Sets an implementation of Notify, that will be notified of the error of each epoch
- setStopError(float) - Method in class AI.NeuralNetworks.BackErrorPropagation
- Sets the stop error
- showList(LinkedList) - Static method in class AI.NeuralNetworks.DistributedBackErrorPropagation
- sigmoid(float) - Static method in class AI.NeuralNetworks.FeedForwardWeightedLayer
- returns the value of the sigmoid function 1/(1+exp(-x))
- size() - Method in class AI.NeuralNetworks.FeedForwardLayer
- Returns the size of the layer including the bias
- sock - Variable in class AI.NeuralNetworks.DistributedBackErrorPropagation
- stopError - Variable in class AI.NeuralNetworks.BackErrorPropagation
T
- toString() - Method in class AI.NeuralNetworks.FeedForwardInputLayer
- returns a String representation of the layer
- toString() - Method in class AI.NeuralNetworks.FeedForwardLayer
- returns a String representation of the layer
- toString() - Method in class AI.NeuralNetworks.FeedForwardNetwork
- retrurns a String representation of the net
- toString() - Method in class AI.NeuralNetworks.FeedForwardWeightedLayer
- returns a String representation of the layer
- toString() - Method in class AI.NeuralNetworks.PatternPair
- returns a string representation of the pattern
- trainNetwork(LinkedList) - Method in class AI.NeuralNetworks.BackErrorPropagation
- Trains the network with the given patterns
- trainNetwork(LinkedList) - Method in class AI.NeuralNetworks.DistributedBackErrorPropagation
- Trains the network with the given patterns
- trainNetwork(LinkedList) - Method in interface AI.NeuralNetworks.NeuralNetworkTeacher
- Trains the network with the given patterns
U
- UnexpectedInputArraySizeException - exception AI.NeuralNetworks.UnexpectedInputArraySizeException.
- UnexpectedInputArraySizeException() - Constructor for class AI.NeuralNetworks.UnexpectedInputArraySizeException
- UnexpectedInputArraySizeException(String) - Constructor for class AI.NeuralNetworks.UnexpectedInputArraySizeException
V
- VECTOR_TOKEN - Static variable in class AI.NeuralNetworks.BackErrorPropagation
- VERSION - Static variable in class AI.NeuralNetworks.FeedForwardNetwork
- VERSION_TOKEN - Static variable in class AI.NeuralNetworks.FeedForwardNetwork
W
- WEIGHTED_LAYER_TOKEN - Static variable in class AI.NeuralNetworks.FeedForwardNetwork
- WEIGHTS_TOKEN - Static variable in class AI.NeuralNetworks.FeedForwardNetwork
- weights - Variable in class AI.NeuralNetworks.FeedForwardWeightedLayer
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