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BiasNeuron
initialises it's input value to -1
ContextNeuron
specifies the memory depth
and sets the input value to 0.5
ContextSynapse
connects two Neurons together,
and sets it's weight to 1
DataProcessor
sets it's inputs
Document
HiddenNeuron
sets the slope of it's activation function
and the number of it's inputs
HiddenNeuron
sets the slope of it's activation function,
the number of it's inputs and the number of delays
InputNeuron
sets the slope of it's activation function
InputNeuron
sets the slope of it's activation function
and the number of delays
MLP
specifies the number of Input Neurons and Hidden Neurons
the slope of their activation functions, the learning rate, the momentum, the number of training
epochs and set a network topology id for use with log files.
OutputFile
OutputNeuron
sets the slope of it's activation function
and the number of it's inputs
RNN
specifies the number of Input Neurons and Hidden Neurons,
the memory depth, the slope of their activation functions, the learning rate, the momentum,
the number of training, epochs and set a network topology id for use with log files.
Synapse
connects two Neurons together,
and sets it's weight to a random value
TDNN
specifies the number of Input Neurons and Hidden Neurons,
the number of delays, the slope of their activation functions, the learning rate, the momentum,
the number of training, epochs and set a network topology id for use with log files.
Test
creates training, testing and validating data sets
XMLParser
builds a new Document
from
an XML file
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