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| Classes in org.joone.engine used by org.joone.engine | |
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| AbstractEventNotifier
This class raises an event notification invoking the corrisponnding Monitor.fireXXX method. |
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| AbstractLearner
This class provides some basic simple functionality that can be used (extended) by other learners. |
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| ContextLayer
The context layer is similar to the linear layer except that it has an auto-recurrent connection between its output and input. |
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| ExtendableLearner
Learners that extend this class are forced to implement certain functions, a so-called skeleton. |
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| ExtendedKalmanFilterFFN
Implements the extended Kalman filter (EKF) as described in "Using an extended Kalman filter learning algorithm for feed-forward neural networks to describe tracer correlations" by Lary and Mussa (2004) in order to train a feed-forward neural network. |
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| ExtendedKalmanFilterRNN
Implements the extended Kalman filter (EKF) as described in "Some observations on the use of the extended Kalman filter as a recurrent network learning algorithm" by Williams (1992) in order to train a recurrent neural network. |
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| FIRFilter
Element of a connection representing a FIR filter (Finite Impulse Response). |
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| FullSynapse
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| InputPatternListener
This interface represents an input synapse for a generic layer. |
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| Layer
The Layer object is the basic element forming the neural net. |
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| Learnable
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| LearnableLayer
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| LearnableSynapse
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| Learner
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| LearnerFactory
Learner factories are used to provide the synapses and layers, through the monitor object with Leaners. |
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| LinearLayer
The output of a linear layer neuron is the sum of the weighted input values, scaled by the beta parameter. |
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| Matrix
The Matrix object represents the connection matrix of the weights of a synapse or the biases of a layer. |
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| MemoryLayer
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| Monitor
The Monitor object is the controller of the behavior of the neural net. |
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| NeuralElement
This interface represents a generic element of a neural network |
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| NeuralLayer
This is the interface for all the layer objects of the neural network |
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| NeuralNetEvent
Transport class used to notify the events raised from a neural network |
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| NeuralNetListener
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| OutputPatternListener
This interface represents an output synapse for a generic layer. |
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| Pattern
The pattern object contains the data that must be processed from a neural net. |
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| RbfGaussianParameters
This class defines the parameters, like center, sigma, etc. |
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| RbfLayer
This is the basis (helper) for radial basis function layers. |
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| RpropParameters
This object holds the global parameters for the RPROP learning algorithm (RpropLearner). |
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| RTRL
A RTRL implementation. |
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| RTRLLearnerFactory.InitialState
An initial state. |
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| RTRLLearnerFactory.Node
A node. |
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| RTRLLearnerFactory.RTRLLearner
The learner we will return from this factory. |
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| RTRLLearnerFactory.Weight
A weight. |
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| SimpleLayer
This abstract class represents layers that are composed by neurons that implement some transfer function. |
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| SpatialMap
SpatialMap is intended to be an abstract spatial map for use with a GaussianLayer. |
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| Synapse
The Synapse is the connection element between two Layer objects. |
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| Classes in org.joone.engine used by org.joone.engine.extenders | |
|---|---|
| ExtendableLearner
Learners that extend this class are forced to implement certain functions, a so-called skeleton. |
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| Matrix
The Matrix object represents the connection matrix of the weights of a synapse or the biases of a layer. |
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| RpropParameters
This object holds the global parameters for the RPROP learning algorithm (RpropLearner). |
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| Classes in org.joone.engine used by org.joone.engine.learning | |
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| Fifo
The Fifo class represents a first-in-first-out
(FIFO) stack of objects. |
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| InputPatternListener
This interface represents an input synapse for a generic layer. |
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| Learnable
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| LearnableSynapse
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| LinearLayer
The output of a linear layer neuron is the sum of the weighted input values, scaled by the beta parameter. |
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| Monitor
The Monitor object is the controller of the behavior of the neural net. |
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| NeuralElement
This interface represents a generic element of a neural network |
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| NeuralNetEvent
Transport class used to notify the events raised from a neural network |
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| OutputPatternListener
This interface represents an output synapse for a generic layer. |
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| Pattern
The pattern object contains the data that must be processed from a neural net. |
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| Synapse
The Synapse is the connection element between two Layer objects. |
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| Classes in org.joone.engine used by org.joone.engine.listeners | |
|---|---|
| Matrix
The Matrix object represents the connection matrix of the weights of a synapse or the biases of a layer. |
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| Monitor
The Monitor object is the controller of the behavior of the neural net. |
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| NeuralNetListener
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| Classes in org.joone.engine used by org.joone.engine.weights | |
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| Matrix
The Matrix object represents the connection matrix of the weights of a synapse or the biases of a layer. |
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| Classes in org.joone.engine used by org.joone.inspection.implementations | |
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| Matrix
The Matrix object represents the connection matrix of the weights of a synapse or the biases of a layer. |
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| Classes in org.joone.engine used by org.joone.io | |
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| Fifo
The Fifo class represents a first-in-first-out
(FIFO) stack of objects. |
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| InputPatternListener
This interface represents an input synapse for a generic layer. |
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| Learnable
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| LearnableSynapse
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| Monitor
The Monitor object is the controller of the behavior of the neural net. |
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| NeuralElement
This interface represents a generic element of a neural network |
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| OutputPatternListener
This interface represents an output synapse for a generic layer. |
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| Pattern
The pattern object contains the data that must be processed from a neural net. |
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| Synapse
The Synapse is the connection element between two Layer objects. |
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| Classes in org.joone.engine used by org.joone.net | |
|---|---|
| InputPatternListener
This interface represents an input synapse for a generic layer. |
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| Layer
The Layer object is the basic element forming the neural net. |
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| Learnable
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| LearnableLayer
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| Matrix
The Matrix object represents the connection matrix of the weights of a synapse or the biases of a layer. |
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| Monitor
The Monitor object is the controller of the behavior of the neural net. |
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| NeuralLayer
This is the interface for all the layer objects of the neural network |
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| NeuralNetEvent
Transport class used to notify the events raised from a neural network |
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| NeuralNetListener
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| OutputPatternListener
This interface represents an output synapse for a generic layer. |
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| Pattern
The pattern object contains the data that must be processed from a neural net. |
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| Classes in org.joone.engine used by org.joone.script | |
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| NeuralNetListener
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| Classes in org.joone.engine used by org.joone.structure | |
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| DirectSynapse
This is forward-only synapse. |
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| InputPatternListener
This interface represents an input synapse for a generic layer. |
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| Layer
The Layer object is the basic element forming the neural net. |
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| Learnable
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| LearnableLayer
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| LearnableSynapse
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| NeuralElement
This interface represents a generic element of a neural network |
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| NeuralLayer
This is the interface for all the layer objects of the neural network |
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| NeuralNetEvent
Transport class used to notify the events raised from a neural network |
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| NeuralNetListener
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| OutputPatternListener
This interface represents an output synapse for a generic layer. |
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| Pattern
The pattern object contains the data that must be processed from a neural net. |
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| Synapse
The Synapse is the connection element between two Layer objects. |
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| Classes in org.joone.engine used by org.joone.util | |
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| InputPatternListener
This interface represents an input synapse for a generic layer. |
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| Learnable
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| LearnableSynapse
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| Monitor
The Monitor object is the controller of the behavior of the neural net. |
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| NeuralElement
This interface represents a generic element of a neural network |
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| NeuralNetEvent
Transport class used to notify the events raised from a neural network |
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| NeuralNetListener
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| OutputPatternListener
This interface represents an output synapse for a generic layer. |
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| Pattern
The pattern object contains the data that must be processed from a neural net. |
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| RbfGaussianLayer
This class implements the nonlinear layer in Radial Basis Function (RBF) networks using Gaussian functions. |
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| RbfGaussianParameters
This class defines the parameters, like center, sigma, etc. |
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| Synapse
The Synapse is the connection element between two Layer objects. |
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