ff_bignet(1)
| ff_bignet(1) | SNNS | ff_bignet(1) |
NAME
ff_bignet - complex network generator for the neural network simulation package SNNS
SYNOPSIS
ff_bignet plane-definition ... link-definition ... [ output-file ]
-p x y [ act [ out [ type ] ] ]
y : number of units in y-direction
act : optional activation function. Default: Act_Logistic
out : optional output function. Default: Out_Identity.
type : optional layer type. Valid types: input, hidden, or output
link-definition
-l source-section target-section
p cx cy cw ch ux uy mx my
cx : x position of cluster in plane p
cy : y position of cluster in plane p
cw : width of cluster in plane p
ch : height of cluster in planep
ux : x position of a distinct unit in plane p
uy : y position of a distinct unit in plane p
mx : delta x for multiple fields in plane p
my : delta y for multiple fields in plane p
Unused parameters have to be specified as 0. A series of 0s at the end of each section may be abreviated by a '+' character.
OPTIONS
output-file
DESCRIPTION
ff_bignet can be used to automatically construct complex neural networks. The synopsis is kind of lengthy, so when networks are to be constructed manually, the graphical version included in xgui(1) is preferrable. The parameters to this tools are derived from the input fields of the bignet panel in xgui(1) If, however, networks are to be constructed automatically, e.g. a whole series from within a shell script, this program is the method of choice. Note that even though the tool is called ff-bignet, it can not only construct feed-forward but also recurrent networks.
EXAMPLES
creates a simple 10-5-6, fully connected feedforward network.
creates the same network including shortcut connections.
creates the same network including additional self recurrent links in the hidden layer.
defines a network with three layers. A 6x20 input layer, a 1x10 hidden layer, and a single output unit. The upper 6x10 input units are fully connected to the hidden layer, which in turn is fully connected to the output unit. The lower 6x10 input units do not have any connections.
defines a 2-3-1 network, fully feed-forward connected with additional self recurrent links in the hidden layer.
SEE ALSO
The SNNS user manual under the SNNS installation directory or the hypertext manual at http://www-ra.informatik.uni-tuebingen.de/SNNS/UserManual/UserManual.html
snns(1) description of the SNNS package
AUTHOR
Guenter W. Mamier
