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