A quick summary of names that can be used for adding NN components in a NN module. These names are available in the current package version. More components can be defined by the user or may be added in future versions.
Layer names currently available include:
generic: a layer of generic Processing Elements (PEs).
generic_d: same as above.
pe: same as above.
pass-through: a layer with PEs that simply pass input to output.
which-max: a layer with PEs that return the index of one of their inputs whose value is maximum.
MAM: a layer with PEs for Matrix-Associative-Memory NNs (see vignette).
LVQ-input: LVQ input layer (see vignette).
LVQ-output: LVQ output layer (see vignette).
BP-hidden: Back-Propagation hidden layer (see vignette).
BP-output: Back-Propagation output layer (see vignette).
R-layer: A layer whose encode and recall (map) functionality is defined in R (see NN_R_components).
Additional (user-defined) layers currently available include:
JustAdd10: a layer where PEs output the sum of their inputs plus 10 (created for use as example in vingnette).
perceptron: a classic perceptron layer (created for use as example in in this post).
MEX: a layer created for use as example in vingnette.
example_layer_0: a layer created to be used as a simple code example for users creating custom layers.
example_layer_1: as above.
example_layer_2: as above.
BP-hidden-softmax: Back-Propagation hidden layer that performs softmax on its output (when recalling).
BP-output-softmax: Back-Propagation output layer that performs softmax on its output (when recalling).
softmax: a layer that (during recall) sums its inputs and outputs the softmax values.
R-connections: A set of connections whose encode and recall (map) functionality is defined in R (see NN_R_components).
Names for connection sets that are currently available include:
generic: a set of generic connections.
pass-through: connections that pass data through with no modification.
wpass-through: connections that pass data multiplied by weight.
MAM: connections for Matrix-Associative-Memory NNs (see vignette).
LVQ: connections for LVQ NNs (see vignette).
BP: connections for Back-Propagation (see vignette).
Additional (user-defined) connection sets currently available include:
perceptron: connections for perceptron (created for use as example in in this post).
MEX: a connection set created for use as example in vingnette.
example_connection_set_0: a connection set created to be used as a simple code example for users creating custom types of connection sets.
example_connection_set_1: as above.
example_connection_set_2: as above.
Vasilis N. Nikolaidis <vnnikolaidis@gmail.com>
NN, NN_R_components.