Encog.Neural.Networks.Synapse

Class	Description
BasicSynapse	An abstract class that implements basic functionality that may be needed by the other synapse classes. Specifically this class handles processing the from and to layer, as well as providing a name and description for the EncogPersistedObject.
DirectSynapse	A direct synapse will present the entire input array to each of the directly connected neurons in the next layer. This layer type is useful when building a radial basis neural network.
OneToOneSynapse	A one-to-one synapse requires that the from and to layers have exactly the same number of neurons. A one-to-one synapse can be useful, when used in conjunction with a ContextLayer.
WeightedSynapse	A fully-connected weight based synapse. Inputs will be multiplied by the weight matrix and presented to the layer. This synapse type is teachable.
WeightlessSynapse	A fully connected synapse that simply sums all input to each neuron, no weights are applied. This synapse type is not teachable.

Interface	Description
ISynapse	A synapse is the connection between two layers of a neural network. The various synapse types define how layers will interact with each other. Some synapses contain a weight matrix, which cause them to be teachable. Others simply feed the data between layers in various ways, and are not teachable.

Enumeration	Description
SynapseType	Specifies the type of synapse to be created.

Encog.Neural.Networks.Synapse Namespace