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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