CMU Artificial Intelligence Repository
SNNS: Stuttgart Neural Network Simulator
areas/neural/systems/snns/
SNNS (Stuttgart Neural Network Simulator) is a software simulator for
neural networks on Unix workstations developed at the Institute for
Parallel and Distributed High Performance Systems (IPVR) at the
University of Stuttgart. The SNNS simulator contains a simulator kernel
written in ANSI C and a 2D/3D graphical user interface running under
X11R4/X11R5.
SNNS includes the following learning procedures: backpropagation
(online, batch, with momentum and flat spot elimin., time delay),
counterpropagation, quickprop, backpercolation 1, and generalized
radial basis functions (RBF), RProp, recurrent ART-1, ART-2 and ARTMAP,
Cascade Correlation and Recurrent Cascade Correlation, Dynamic LVQ,
and Time delay networks (TDNN). (Elman networks and some other network
paradigms have already been implemented but are scheduled for a later
release.)
NESSUS is a language for the description of neural networks. The
Nessus compiler creates a network description that can be read by SNNS.
SNNS2C is a tool to convert the description of a neural network
from SNNS format to C source code. This code can then be linked to an
existing program as a subroutine.
SNNS is among the most popular neural network simulators.
Origin:
ftp.informatik.uni-stuttgart.de:/pub/SNNS/ [129.69.211.2].
as the files SNNSv2.1.tar.Z, SNNSv2.1.Manual.ps.Z,
SNNS2Cv2.1.tar.Z, and NESSUSv2.1.tar.Z
Version: SNNS 3.1; Nessus 2.1; SNNS2C 2.1
Requires: ANSI C, X11
Ports: It runs under Sun Sparc (SLC, ELC, SS2, GX, GS),
DECstation (2100, 3100, 5000/200), IBM RS 6000, HP 9000,
and IBM-PC (386/486).
Copying: Copyright (c) 1990-93 University of Stuttgart, IPVR, FRG.
Use, copying, and distribution permitted. Modification
prohibited. (Modifications may be distributed as
separate patch files.)
CD-ROM: Prime Time Freeware for AI, Issue 1-1
Mailing List: snns@informatik.uni-stuttgart.de
To be added to the mailing list, send a message to
listserv@informatik.uni-stuttgart.de
with
subscribe snns
in the message body.
Author(s): Andreas Zell
Guenter Mamier
University of Stuttgart, IPVR
Breitwiesenstrasse 20-22,
W-7000 Stuttgart 80, Germany
Keywords:
ART-1, ART-2, ARTMAP, Authors!Mamier, Authors!Zell,
Backpercolation, Backpropagation, C!Code,
Cascade Correlation, Counterpropagation, Dynamic LVQ, LVQ,
Machine Learning!Neural Networks, NESSUS, NETtalk,
Neural Networks!Description Languages,
Neural Networks!Simulators, Quickprop, RBF, RProp,
Radial Basis Functions, Recurrent ART-1,
Recurrent Cascade Correlation, SNNS,
Stuttgart Neural Network Simulator, TDNN,
Time Delay Neural Networks
References: ?
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