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On Thu, 29 Oct 1998 Sethw2@xxxxxxx wrote:
> I am looking for a simple to use Neural Net package (preferably for Windows)
> that is available through freeware or shareware. I am not a programmer...
>
Seth,
Check out SNNS. Here is a blurb re the recent release. If you are a POB,
you will be a revision behind.
Cheers,
Jim
**********************************************************************
The new version 4.2 of SNNS is available now (thanks to the work of
Guenter Mamier and Michael Vogt and several external contributors)!
**********************************************************************
What is SNNS ?
**********************************************************************
SNNS (Stuttgart Neural Network Simulator) is a software simulator for
neural networks on Unix PCs and workstations, originally developed at
the Inst. for Parallel and Distributed High Performance Systems (IPVR)
at the University of Stuttgart, and further developed at CERN and at
the University of Tuebingen, Wilhelm-Schickard-Institute for Computer
Science. The goal of the SNNS project was to create an efficient and
flexible simulation environment for research on and application of
artificial neural networks.
The SNNS simulator consists of two main components:
1) simulator kernel written in C
2) graphical user interface under X11R6
The simulator kernel operates on the internal network data structures
of the neural nets and performs all operations of learning and recall.
It can also be used without the other parts as a C program embedded in
custom applications. It supports arbitrary network topologies.
SNNS can be extended with user defined activation functions, output
functions, site functions and learning procedures, which are written
as simple C programs and linked to the simulator kernel.
Currently the following network architectures and learning procedures
are included:
* Backpropagation (BP) for feedforward networks
vanilla (online) BP
BP with momentum term and flat spot elimination
batch BP
BP with Chunkwise Updating
* Counterpropagation
* Quickprop
* Backpercolation 1
* RProp
* RProp with Weight Decay
* Generalized radial basis functions (RBF)
* ART1
* ART2
* ARTMAP
* Cascade Correlation
* Dynamic LVQ
* Backpropagation through time (for recurrent networks)
* Quickprop through time (for recurrent networks)
* Self-organizing maps (Kohonen maps)
* TDNN (time-delay networks) with Backpropagation
* Jordan networks
* Elman networks and extended hierarchical Elman networks
* Associative Memory
* RBF_DDA
* Simulated Annealing
* Monte Carlo.
* Pruned-Cascade-Correlation
A number of network pruning algorithms are available as well:
* Optimal Brain Damage (OBD),
* Optimal Brain Surgeon (OBS),
* Skeletonization,
* Magnitute based pruning (Mag).
The graphical user interface XGUI (X Graphical User Interface), built
on top of the kernel, gives a 2D and a 3D graphical representation of
the neural networks and controls the kernel during the simulation run.
In addition, the 2D user interface has an integrated network editor
which can be used to directly create, manipulate and visualize neural
nets in various ways.
**********************************************************************
New features of SNNSv4.2
**********************************************************************
Version 4.2 of SNNS features the following improvements and extensions
over the earlier version 4.1:
* greatly improved installation procedure
* pattern remapping functions introduced to SNNS
* class information in patterns introduced to SNNS
* change to all batch algorithms: The learning rate is now divided by
the number of patterns in the set. This allows for direct comparisons
of learning rates and training of large pattern files with BP-Batch
since it doesn't require ridiculous learning rates like 0.0000001
anymore.
* Changes to Cascade-Correlation:
-- Several modifications can be used to achieve a net with a smaller
depth or smaller fan-in.
-- New activation functions ACT_GAUSS and ACT_SIN
-- The backpropagation algorithm of Cascade-Correlation is now
available in an off-line and a batch version.
-- The activations of the units can be cached. The result is a faster
learning for nets with many units. On the other hand, the
necessary memory space will increase for large pattern sets.
-- Changes in the 2D-display, the hidden units are displayed in
layers, the candidate units are placed on the top of the net.
-- validation now possible
-- automatic deletion of candidate units at the end of training.
* new meta learning algorithm TACOMA.
* new learning algorithm BackpropChunk. It allows chunkwise updating of
the weights as well as selective training of units on the basis of
pattern class names.
* new learning algorithm RPROP with weight decay.
* algorithm "Recurrent Cascade Correlation" deleted from repository.
* the options of adding noise to the weights with the JogWeights
function improved im multiple ways.
* improved plotting in the graph panel as well as printing option.
* when standard colormap is full, SNNS will now start with a privat map
instead of aborting.
* analyze tool now features a confusion matrix.
* pruning panel now more "SNNS-like". You do not need to close
the panel anymore before pruning a network.
* Changes in batchman
-- batchman can now handle DLVQ training
-- new batchman command "setActFunc" allows the changing of unit
activation functions from within the training script.
-- batchman output now with "\#" prefix. This enables direct
processing by a lot of unix tools like gnuplot.
-- batchman now automatically converts function parameters to
correct type instead of aborting.
-- jogWeights can now also be called from batchman.
-- batchman catches some non-fatal signals (SIGINT, SIGTERM, ...)
and sets the internal variable SIGNAL so that the script can react
to them.
-- batchman features ResetNet function (e.g. for Jordan networks).
* new tool "linknets" introduced to combine existing networks.
* new tools "td_bignet" and "ff_bignet" introduced for script-based
generation of network files; Old tool "bignet" removed.
* displays will be refreshed more often when using the graphical editor
* weight and projection display with changed color scale. They now
match the 2D-display scale.
* pat_sel now can handle pattern files with multi-line comments
* manpages now available for most of the SNNS programs.
* the number of things stored in an xgui configuration file was
greatly enhanced.
* Extensive debugging:
-- batchman computes MSE now correctly from the number of (sub-)
patterns.
-- RBFs receive now correct number of parameters.
-- spurious segmentation faults in the graphical editor tracked and
eliminated.
-- segmentation fault when training on huge pattern files cleared.
-- various seg-faults under single operating systems tracked and
cleared.
-- netperf now can test on networks that need multiple training
parameters.
-- segmentaion faults when displaying 3D-Networks cleared.
-- correct default values for initialization functions in batchman.
-- the call "TestNet()" prohibited further training in batchman.
Now everything works as expected.
-- segmentation fault in batchman when doing multiple string concats
cleared and memory leak in string operations closed.
-- the output of the validation error on the shell window was giving
wrong values.
-- algorithm SCG now respects special units and handles them correctly
-- the description of the learning function parameters in section 4.4
is finally ordered alphabetically.
**********************************************************************
Machine architectures on which SNNSv4.2 is available
**********************************************************************
SNNSv4.2 should run on the following machines and operating systems:
machine type OS
SUN Ultra 1, 2, 5, 10, ... Solaris 2.5.1, ...
SGI O2, Octane, Origin IRIX 5.2, ...
DEC Alpha Digital Unix
IBM RS 6000 AIX 4.2.1, 4.3, ...
HP 9000, 8xx HP/UX 9.x, 10.x (not tested)
PC Pentium, Pentium MMX, PII Linux (S.u.S.E 2.0.33), FreeBSD
If you successfully run SNNSv4.2 under a different architecture or
OS version please send a mail to fischer@xxxxxxxxxxxxxxxxxxxxxxxxxxx
We plan to set up a detailed table on our SNNS WWW page soon.
**********************************************************************
SNNSv4.2 licensing terms (short)
**********************************************************************
SNNSv4.2 is available NOW free of charge for research purposes under a
GNU-style copyright agreement. See the license agreement in the user
manual and in the file Readme.license of the distribution for details.
SNNS is (C) (Copyright) 1990-96 SNNS Group, Institute for Parallel and
Distributed High-Performance Systems (IPVR), University of Stuttgart,
Breitwiesenstrasse 20-22, 70565 Stuttgart, Germany, and (C) (Copyright)
1996-98 SNNS Group, Wilhelm Schickard Institute for Computer Science,
University of Tuebingen, Koestlinstr. 6, D-72074 Tuebingen, Germany.
SNNSv4.2 can only be obtained by anonymous ftp over the Internet. See
the detailed description of how to obtain SNNS below. We don't have
the time and capacity to send tapes or floppy disks, so don't ask.
SNNSv4.2 is also too large to be mailed by e-mail, so don't ask for
that, either. You may, however, obtain the unmodified SNNSv4.2
distribution from other sites which already have obtained it, under
the terms of our license agreement, if you are unable to connect to
our machine.
Note that SNNS has not been tested extensively in different computer
environments and is a research tool.
It should be obvious that WE DO NOT GUARANTEE ANYTHING.
We are also not staffed to answer problems with SNNS or to fix bugs
quickly. For questions and/or comments concerning SNNS we refer you to
the SNNS mailing list. To subscribe, send a mail to
SNNS-Mail-Request@xxxxxxxxxxxxxxxxxxxxxxxxxxx
With the one line message (in the mail body, not in the subject)
subscribe
SNNSv4.2 may be put on Linux software distributions, provided that all
authors are named in the order of the SNNSv4.2 user manual title page
and that the University of Tuebingen, WSI, Prof. A. Zell, Koestlinstr.
6, D-72074 Tuebingen, Germany, receives a free complimentary copy of
every new distribution on CD.
**********************************************************************
How to obtain SNNSv4.2
**********************************************************************
The SNNS simulator can be obtained via anonymous ftp from host
ftp.informatik.uni-tuebingen.de (129.69.211.2)
in the subdirectory /pub/SNNS
in gzipped form as file
SNNSv4.2.tar.gz (2.18 MB)
Be sure to set the ftp mode to binary before transmission of the
files. Also watch out for possible higher version numbers, patches or
Readme files in the above directory /pub/SNNS . After successful
transmission of the file move it to the directory where you want to
install SNNS, uncompress and extract the file with the Unix command
tar xvfz SNNSv4.2.tar.gz
The SNNS distribution includes full source code, installation
procedures for supported machine architectures and some simple
examples of trained networks.
The PostScript version of the user manual can be obtained as file
SNNSv4.2.Manual.ps.gz (1.35 MB)
There is also an (older) Implementation Manual available as file
SNNSv4.1.Implem.ps.Z (0.24 MB)
More information about SNNS as well as a html version of the manual can
be found at
http://www-ra.informatik.uni-tuebingen.de/SNNS/
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