Contains an identifier id which must be unique in all layers. The attribute bias implicitly defines a connection to
a bias unit where the unit's value is 1.0 and the weight is the value of bias. The activation function and
normalization method for Neuron can be defined in NeuralLayer. If either one is not defined for the layer then the
default one specified for NeuralNetwork applies. If the activation function is radialBasis, the attribute width must
be specified either in Neuron, NeuralLayer or NeuralNetwork. Again, width specified in Neuron will override a
respective value from NeuralLayer, and in turn will override a value given in NeuralNetwork.
Weighted connections between neural net nodes are represented by Con elements.
Contains an identifier id which must be unique in all layers. The attribute bias implicitly defines a connection to a bias unit where the unit's value is 1.0 and the weight is the value of bias. The activation function and normalization method for Neuron can be defined in NeuralLayer. If either one is not defined for the layer then the default one specified for NeuralNetwork applies. If the activation function is radialBasis, the attribute width must be specified either in Neuron, NeuralLayer or NeuralNetwork. Again, width specified in Neuron will override a respective value from NeuralLayer, and in turn will override a value given in NeuralNetwork.
Weighted connections between neural net nodes are represented by Con elements.