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From: saswss@unx.sas.com (Warren Sarle)
Subject: comp.ai.neural-nets FAQ, Part 5 of 7: Free software
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Archive-name: ai-faq/neural-nets/part5
Last-modified: 1996-01-17
URL: ftp://ftp.sas.com/pub/neural/FAQ5.html
Maintainer: saswss@unx.sas.com (Warren S. Sarle)

This is part 5 (of 7) of a monthly posting to the Usenet newsgroup
comp.ai.neural-nets. See the part 1 of this posting for full information
what it is all about.

========== Questions ========== 
********************************

Part 1: Introduction

   What is this newsgroup for? How shall it be used?
   What is a neural network (NN)?
   What can you do with a Neural Network and what not?
   Who is concerned with Neural Networks?

Part 2: Learning

   What does 'backprop' mean? What is 'overfitting'?
   Why use a bias input? Why activation functions?
   How many hidden units should I use?
   How many learning methods for NNs exist? Which?
   What about Genetic Algorithms and Evolutionary Computation?
   What about Fuzzy Logic?
   How are NNs related to statistical methods?

Part 3: Information resources

   Good introductory literature about Neural Networks?
   Any journals and magazines about Neural Networks?
   The most important conferences concerned with Neural Networks?
   Neural Network Associations?
   Other sources of information about NNs?

Part 4: Datasets

   Databases for experimentation with NNs?

Part 5: Free software

   Freely available software packages for NN simulation?

Part 6: Commercial software

   Commercial software packages for NN simulation?

Part 7: Hardware

   Neural Network hardware?

------------------------------------------------------------------------

Subject: Freely available software packages for NN
==================================================
simulation?
===========

Note for future submissions: Please restrict yourself to 60 lines length.
Please send a HTML-formatted version if at all possible. 

The following simulators are described below: 

1. Rochester Connectionist Simulator 
2. UCLA-SFINX 
3. NeurDS 
4. PlaNet (formerly known as SunNet) 
5. GENESIS 
6. Mactivation 
7. Cascade Correlation Simulator 
8. Quickprop 
9. DartNet 
10. SNNS 
11. Aspirin/MIGRAINES 
12. Adaptive Logic Network Educational Kit 
13. NeuralShell 
14. PDP++ 
15. Uts (Xerion, the sequel) 
16. Neocognitron simulator 
17. Multi-Module Neural Computing Environment (MUME) 
18. LVQ_PAK, SOM_PAK 
19. SESAME 
20. Nevada Backpropagation (NevProp) 
21. Fuzzy ARTmap 
22. PYGMALION 
23. Basis-of-AI-backprop 
24. Matrix Backpropagation 
25. WinNN 
26. BIOSIM 
27. The Brain 
28. FuNeGen 
29. NeuDL -- Neural-Network Description Language 
30. NeoC Explorer 
31. AINET 

Here are the full descriptions and references: 

1. Rochester Connectionist Simulator
++++++++++++++++++++++++++++++++++++

   A quite versatile simulator program for arbitrary types of neural nets.
   Comes with a backprop package and a X11/Sunview interface. Available via
   anonymous FTP from cs.rochester.edu in directory pub/packages/simulator
   as the files README (8 KB), rcs_v4.2.tar.Z (2.9 MB), 

2. UCLA-SFINX
+++++++++++++

   ftp retina.cs.ucla.edu [131.179.16.6]; Login name: sfinxftp; Password:
   joshua; directory: pub; files : README; sfinx_v2.0.tar.Z; Email info
   request : sfinx@retina.cs.ucla.edu 

3. NeurDS
+++++++++

   simulator for DEC systems supporting VT100 terminal. available for
   anonymous ftp from gatekeeper.dec.com [16.1.0.2] in directory: pub/DEC as
   the file NeurDS031.tar.Z (111 Kb) 

4. PlaNet5.7 (formerly known as SunNet)
+++++++++++++++++++++++++++++++++++++++

   A popular connectionist simulator with versions to run under X Windows,
   and non-graphics terminals created by Yoshiro Miyata (Chukyo Univ.,
   Japan). 60-page User's Guide in Postscript. Send any questions to
   miyata@sccs.chukyo-u.ac.jp Available for anonymous ftp from
   ftp.ira.uka.de as /pub/neuron/PlaNet5.7.tar.Z (800 kb) or from
   boulder.colorado.edu [128.138.240.1] as 
   /pub/generic-sources/PlaNet5.7.tar.Z 

5. GENESIS
++++++++++

   GENESIS 2.0 (GEneral NEural SImulation System) is a general purpose
   simulation platform which was developed to support the simulation of
   neural systems ranging from complex models of single neurons to
   simulations of large networks made up of more abstract neuronal
   components. Most current GENESIS applications involve realistic
   simulations of biological neural systems. Although the software can also
   model more abstract networks, other simulators are more suitable for
   backpropagation and similar connectionist modeling. Runs on most Unix
   platforms. Graphical front end XODUS. Parallel version for networks of
   workstations, symmetric multiprocessors, and MPPs also available.
   Available by ftp from ftp://genesis.bbb.caltech.edu/pub/genesis. Further
   information via WWW at http://www.bbb.caltech.edu/GENESIS/. 

6. Mactivation
++++++++++++++

   A neural network simulator for the Apple Macintosh. Available for ftp
   from ftp.cs.colorado.edu [128.138.243.151] as 
   /pub/cs/misc/Mactivation-3.3.sea.hqx 

7. Cascade Correlation Simulator
++++++++++++++++++++++++++++++++

   A simulator for Scott Fahlman's Cascade Correlation algorithm. Available
   for ftp from ftp.cs.cmu.edu in directory
   /afs/cs/project/connect/code/supported as the file cascor-v1.2.shar (223
   KB) There is also a version of recurrent cascade correlation in the same
   directory in file rcc1.c (108 KB). 

8. Quickprop
++++++++++++

   A variation of the back-propagation algorithm developed by Scott Fahlman.
   A simulator is available in the same directory as the cascade correlation
   simulator above in file nevprop1.16.shar (137 KB)
   (There is also an obsolete simulator called quickprop1.c (21 KB) in the
   same directory, but it has been superseeded by NevProp. See also the
   description of NevProp below.) 

9. DartNet
++++++++++

   DartNet is a Macintosh-based backpropagation simulator, developed at
   Dartmouth by Jamshed Bharucha and Sean Nolan as a pedagogical tool. It
   makes use of the Mac's graphical interface, and provides a number of
   tools for building, editing, training, testing and examining networks.
   This program is available by anonymous ftp from dartvax.dartmouth.edu
   [129.170.16.4] as /pub/mac/dartnet.sit.hqx (124 KB). 

10. SNNS
++++++++

   "Stuttgart Neural Network Simulator" from the University of Stuttgart,
   Germany. A luxurious simulator for many types of nets; with X11
   interface: Graphical 2D and 3D topology editor/visualizer, training
   visualisation, multiple pattern set handling etc. Currently supports
   backpropagation (vanilla, online, with momentum term and flat spot
   elimination, batch, time delay), counterpropagation, quickprop,
   backpercolation 1, generalized radial basis functions (RBF), RProp, ART1,
   ART2, ARTMAP, Cascade Correlation, Recurrent Cascade Correlation, Dynamic
   LVQ, Backpropagation through time (for recurrent networks), batch
   backpropagation through time (for recurrent networks), Quickpropagation
   through time (for recurrent networks), Hopfield networks, Jordan and
   Elman networks, autoassociative memory, self-organizing maps, time-delay
   networks (TDNN), RBF_DDA, simulated annealing, Monte Carlo, Pruned
   Cascade-Correlation, Optimal Brain Damage, Optimal Brain Surgeon,
   Skeletonization, and is user-extendable (user-defined activation
   functions, output functions, site functions, learning procedures). C code
   generator snns2c. Works on SunOS, Solaris, IRIX, Ultrix, OSF, AIX, HP/UX,
   NextStep, and Linux. Distributed kernel can spread one learning run over
   a workstation cluster. Available for ftp from
   ftp.informatik.uni-stuttgart.de [129.69.211.2] in directory /pub/SNNS as 
   SNNSv4.0.tar.gz (1.4 MB, Source code) and SNNSv4.0.Manual.ps.gz (1 MB,
   Documentation). There are also various other files in this directory
   (e.g. the source version of the manual, a Sun Sparc executable, older
   versions of the software, some papers, an implementation manual, and the
   software in several smaller parts). It may be best to first have a look
   at the file SNNSv4.0.Readme. This file contains a somewhat more elaborate
   short description of the simulator. More information can be found in the
   WWW under http://vasarely.informatik.uni-stuttgart.de/snns/snns.html 

11. Aspirin/MIGRAINES
+++++++++++++++++++++

   Aspirin/MIGRAINES 6.0 consists of a code generator that builds neural
   network simulations by reading a network description (written in a
   language called "Aspirin") and generates a C simulation. An interface
   (called "MIGRAINES") is provided to export data from the neural network
   to visualization tools. The system has been ported to a large number of
   platforms. The goal of Aspirin is to provide a common extendible
   front-end language and parser for different network paradigms. The
   MIGRAINES interface is a terminal based interface that allows you to open
   Unix pipes to data in the neural network. Users can display the data
   using either public or commercial graphics/analysis tools. Example
   filters are included that convert data exported through MIGRAINES to
   formats readable by Gnuplot 3.0, Matlab, Mathematica, and xgobi. The
   software is available from two FTP sites: from CMU's simulator collection
   on pt.cs.cmu.edu [128.2.254.155] in 
   /afs/cs/project/connect/code/am6.tar.Z and from UCLA's cognitive science
   machine ftp.cognet.ucla.edu [128.97.50.19] in /pub/alexis/am6.tar.Z (2
   MB). 

12. Adaptive Logic Network Educational Kit (for Windows)
++++++++++++++++++++++++++++++++++++++++++++++++++++++++

   This package differs from the traditional nets in that it uses logic
   functions AND and OR in all hidden layers but the first, which uses
   simple perceptrons. This representation of functions from real valued
   inputs to real outputs allows the user to impose constraints on the
   learned solution (monotonicity, convexity,...). Execution software is
   provided in C source form for experimenters. Anonymous ftp from
   ftp.cs.ualberta.ca in directory /pub/atree/atree3/. See files 
   atree3ek.exe and atree3ek.brief.guide, This software is the same as the
   commercial Atree 3.0 program for functions of one or two inputs. 

13. NeuralShell
+++++++++++++++

   Formerly available from FTP site quanta.eng.ohio-state.edu [128.146.35.1]
   as /pub/NeuralShell/NeuralShell.tar". Currently (April 94) not available
   and undergoing a major reconstruction. Not to be confused with NeuroShell
   by Ward System Group (see below under commercial software). 

14. PDP++
+++++++++

   The PDP++ software is a new neural-network simulation system written in
   C++. It represents the next generation of the PDP software released with
   the McClelland and Rumelhart "Explorations in Parallel Distributed
   Processing Handbook", MIT Press, 1987. It is easy enough for novice
   users, but very powerful and flexible for research use.
   The current version is 1.0, our first non-beta release. It has been
   extensively tested and should be completely usable. Works on Unix with
   X-Windows.
   Features: Full GUI (InterViews), realtime network viewer, data viewer,
   extendable object-oriented design, CSS scripting language with
   source-level debugger, GUI macro recording. 
   Algorithms: Feedforward and several recurrent BP, Boltzmann machine,
   Hopfield, Mean-field, Interactive activation and competition, continuous
   stochastic networks. 
   The software can be obtained by anonymous ftp from 
   ftp://hydra.psy.cmu.edu/pub/pdp++/ and from 
   ftp://unix.hensa.ac.uk/mirrors/pdp++/.
   For more information, see our WWW page at 
   http://www.cs.cmu.edu/Web/Groups/CNBC/PDP++/PDP++.html.
   There is a 250 page (printed) manual and an HTML version available
   on-line at the above address. 

15. Uts (Xerion, the sequel)
++++++++++++++++++++++++++++

   Uts is a portable artificial neural network simulator written on top of
   the Tool Control Language (Tcl) and the Tk UI toolkit. As result, the
   user interface is readily modifiable and it is possible to simultaneously
   use the graphical user interface and visualization tools and use scripts
   written in Tcl. Uts itself implements only the connectionist paradigm of
   linked units in Tcl and the basic elements of the graphical user
   interface. To make a ready-to-use package, there exist modules which use
   Uts to do back-propagation (tkbp) and mixed em gaussian optimization
   (tkmxm). Uts is available in ftp.cs.toronto.edu in directory /pub/xerion.

16. Neocognitron simulator
++++++++++++++++++++++++++

   The simulator is written in C and comes with a list of references which
   are necessary to read to understand the specifics of the implementation.
   The unsupervised version is coded without (!) C-cell inhibition.
   Available for anonymous ftp from unix.hensa.ac.uk [129.12.21.7] in 
   /pub/neocognitron.tar.Z (130 kB). 

17. Multi-Module Neural Computing Environment (MUME)
++++++++++++++++++++++++++++++++++++++++++++++++++++

   MUME is a simulation environment for multi-modules neural computing. It
   provides an object oriented facility for the simulation and training of
   multiple nets with various architectures and learning algorithms. MUME
   includes a library of network architectures including feedforward, simple
   recurrent, and continuously running recurrent neural networks. Each
   architecture is supported by a variety of learning algorithms. MUME can
   be used for large scale neural network simulations as it provides support
   for learning in multi-net environments. It also provide pre- and
   post-processing facilities. The modules are provided in a library.
   Several "front-ends" or clients are also available. X-Window support by
   editor/visualization tool Xmume. MUME can be used to include non-neural
   computing modules (decision trees, ...) in applications. MUME is
   available for educational institutions by anonymous ftp on
   mickey.sedal.su.oz.au [129.78.24.170] after signing and sending a
   licence: /pub/license.ps (67 kb). Contact: Marwan Jabri, SEDAL, Sydney
   University Electrical Engineering, NSW 2006 Australia,
   marwan@sedal.su.oz.au 

18. LVQ_PAK, SOM_PAK
++++++++++++++++++++

   These are packages for Learning Vector Quantization and Self-Organizing
   Maps, respectively. They have been built by the LVQ/SOM Programming Team
   of the Helsinki University of Technology, Laboratory of Computer and
   Information Science, Rakentajanaukio 2 C, SF-02150 Espoo, FINLAND There
   are versions for Unix and MS-DOS available from cochlea.hut.fi
   [130.233.168.48] as /pub/lvq_pak/lvq_pak-2.1.tar.Z (340 kB, Unix sources),
   /pub/lvq_pak/lvq_p2r1.exe (310 kB, MS-DOS self-extract archive), 
   /pub/som_pak/som_pak-1.2.tar.Z (251 kB, Unix sources), 
   /pub/som_pak/som_p1r2.exe (215 kB, MS-DOS self-extract archive). (further
   programs to be used with SOM_PAK and LVQ_PAK can be found in /pub/utils).

19. SESAME
++++++++++

   ("Software Environment for the Simulation of Adaptive Modular Systems")
   SESAME is a prototypical software implementation which facilitates 
    o Object-oriented building blocks approach. 
    o Contains a large set of C++ classes useful for neural nets,
      neurocontrol and pattern recognition. No C++ classes can be used as
      stand alone, though! 
    o C++ classes include CartPole, nondynamic two-robot arms, Lunar Lander,
      Backpropagation, Feature Maps, Radial Basis Functions, TimeWindows,
      Fuzzy Set Coding, Potential Fields, Pandemonium, and diverse utility
      building blocks. 
    o A kernel which is the framework for the C++ classes and allows
      run-time manipulation, construction, and integration of arbitrary
      complex and hybrid experiments. 
    o Currently no graphic interface for construction, only for
      visualization. 
    o Platform is SUN4, XWindows 
   Unfortunately no reasonable good introduction has been written until now.
   We hope to have something soon. For now we provide papers (eg. NIPS-92),
   a reference manual (>220 pages), source code (ca. 35.000 lines of code),
   and a SUN4-executable by ftp only. Sesame and its description is
   available in various files for anonymous ftp on ftp ftp.gmd.de in the
   directories /gmd/as/sesame and /gmd/as/paper. Questions to
   sesame-request@gmd.de; there is only very limited support available. 

20. Nevada Backpropagation (NevProp)
++++++++++++++++++++++++++++++++++++

   NevProp is a free, easy-to-use feedforward backpropagation (multilayer
   perceptron) program. It uses an interactive character-based interface,
   and is distributed as C source code that should compile and run on most
   platforms. (Precompiled executables are available for Macintosh and DOS.)
   The original version was Quickprop 1.0 by Scott Fahlman, as translated
   from Common Lisp by Terry Regier. We added early-stopped training based
   on a held-out subset of data, c index (ROC curve area) calculation, the
   ability to force gradient descent (per-epoch or per-pattern), and
   additional options. FEATURES (NevProp version 1.16): UNLIMITED (except by
   machine memory) number of input PATTERNS; UNLIMITED number of input,
   hidden, and output UNITS; Arbitrary CONNECTIONS among the various layers'
   units; Clock-time or user-specified RANDOM SEED for initial random
   weights; Choice of regular GRADIENT DESCENT or QUICKPROP; Choice of
   PER-EPOCH or PER-PATTERN (stochastic) weight updating; GENERALIZATION to
   a test dataset; AUTOMATICALLY STOPPED TRAINING based on generalization;
   RETENTION of best-generalizing weights and predictions; Simple but useful
   GRAPHIC display to show smoothness of generalization; SAVING of results
   to a file while working interactively; SAVING of weights file and
   reloading for continued training; PREDICTION-only on datasets by applying
   an existing weights file; In addition to RMS error, the concordance, or c
   index is displayed. The c index (area under the ROC curve) shows the
   correctness of the RELATIVE ordering of predictions AMONG the cases; ie,
   it is a measure of discriminative power of the model. AVAILABILITY: The
   most updated version of NevProp will be made available by anonymous ftp
   from the University of Nevada, Reno: On ftp.scs.unr.edu [134.197.10.130]
   in the directory "pub/goodman/nevpropdir", e.g. README.FIRST (45 kb) or 
   nevprop1.16.shar (138 kb). Version 2 (not yet released) is intended to
   have some new features: more flexible file formatting (including access
   to external data files; option to prerandomize data order; randomized
   stochastic gradient descent; option to rescale predictor (input)
   variables); linear output units as an alternative to sigmoidal units for
   use with continuous-valued dependent variables (output targets);
   cross-entropy (maximum likelihood) criterion function as an alternative
   to square error for use with categorical dependent variables
   (classification/symbolic/nominal targets); and interactive interrupt to
   change settings on-the-fly. Limited support is available from Phil
   Goodman (goodman@unr.edu), University of Nevada Center for Biomedical
   Research. 

21. Fuzzy ARTmap
++++++++++++++++

   This is just a small example program. Available for anonymous ftp from
   park.bu.edu [128.176.121.56] /pub/fuzzy-artmap.tar.Z (44 kB). 

22. PYGMALION
+++++++++++++

   This is a prototype that stems from an ESPRIT project. It implements
   back-propagation, self organising map, and Hopfield nets. Avaliable for
   ftp from ftp.funet.fi [128.214.248.6] as 
   /pub/sci/neural/sims/pygmalion.tar.Z (1534 kb). (Original site is
   imag.imag.fr: archive/pygmalion/pygmalion.tar.Z). 

23. Basis-of-AI-backprop
++++++++++++++++++++++++

   Earlier versions have been posted in comp.sources.misc and people around
   the world have used them and liked them. This package is free for
   ordinary users but shareware for businesses and government agencies
   ($200/copy, but then for this you get the professional version as well).
   I do support this package via email. Some of the highlights are: 
    o in C for UNIX and DOS and DOS binaries 
    o gradient descent, delta-bar-delta and quickprop 
    o extra fast 16-bit fixed point weight version as well as a conventional
      floating point version 
    o recurrent networks 
    o numerous sample problems 
   Available for ftp from ftp.mcs.com in directory /mcsnet.users/drt. Or see
   the WWW page http://www.mcs.com/~drt/home.html. The expanded professional
   version is $30/copy for ordinary individuals including academics and
   $200/copy for businesses and government agencies (improved user
   interface, more activation functions, networks can be read into your own
   programs, dynamic node creation, weight decay, SuperSAB). More details
   can be found in the documentation for the student version. Contact: Don
   Tveter; 5228 N. Nashville Ave.; Chicago, Illinois 60656; drt@mcs.com 

24. Matrix Backpropagation
++++++++++++++++++++++++++

   MBP (Matrix Back Propagation) is a very efficient implementation of the
   back-propagation algorithm for current-generation workstations. The
   algorithm includes a per-epoch adaptive technique for gradient descent.
   All the computations are done through matrix multiplications and make use
   of highly optimized C code. The goal is to reach almost peak-performances
   on RISCs with superscalar capabilities and fast caches. On some machines
   (and with large networks) a 30-40x speed-up can be measured with respect
   to conventional implementations. The software is available by anonymous
   ftp from risc6000.dibe.unige.it [130.251.89.154] as /pub/MBPv1.1.tar.Z
   (Unix version), /pub/MBPv11.zip.Z (MS-DOS version), /pub/mpbv11.ps
   (Documentation). For more information, contact Davide Anguita
   (anguita@dibe.unige.it). 

25. WinNN
+++++++++

   WinNN is a shareware Neural Networks (NN) package for windows 3.1. WinNN
   incorporates a very user friendly interface with a powerful computational
   engine. WinNN is intended to be used as a tool for beginners and more
   advanced neural networks users, it provides an alternative to using more
   expensive and hard to use packages. WinNN can implement feed forward
   multi-layered NN and uses a modified fast back-propagation for training.
   Extensive on line help. Has various neuron functions. Allows on the fly
   testing of the network performance and generalization. All training
   parameters can be easily modified while WinNN is training. Results can be
   saved on disk or copied to the clipboard. Supports plotting of the
   outputs and weight distribution. Available for ftp from
   ftp.cc.monash.edu.au as /pub/win3/programr/winnn97.zip (747 kB). 

26. BIOSIM
++++++++++

   BIOSIM is a biologically oriented neural network simulator. Public
   domain, runs on Unix (less powerful PC-version is available, too), easy
   to install, bilingual (german and english), has a GUI (Graphical User
   Interface), designed for research and teaching, provides online help
   facilities, offers controlling interfaces, batch version is available, a
   DEMO is provided. REQUIREMENTS (Unix version): X11 Rel. 3 and above,
   Motif Rel 1.0 and above, 12 MB of physical memory, recommended are 24 MB
   and more, 20 MB disc space. REQUIREMENTS (PC version): PC-compatible with
   MS Windows 3.0 and above, 4 MB of physical memory, recommended are 8 MB
   and more, 1 MB disc space. Four neuron models are implemented in BIOSIM:
   a simple model only switching ion channels on and off, the original
   Hodgkin-Huxley model, the SWIM model (a modified HH model) and the
   Golowasch-Buchholz model. Dendrites consist of a chain of segments
   without bifurcation. A neural network can be created by using the
   interactive network editor which is part of BIOSIM. Parameters can be
   changed via context sensitive menus and the results of the simulation can
   be visualized in observation windows for neurons and synapses. Stochastic
   processes such as noise can be included. In addition, biologically
   orientied learning and forgetting processes are modeled, e.g.
   sensitization, habituation, conditioning, hebbian learning and
   competitive learning. Three synaptic types are predefined (an
   excitatatory synapse type, an inhibitory synapse type and an electrical
   synapse). Additional synaptic types can be created interactively as
   desired. Available for ftp from ftp.uni-kl.de in directory
   /pub/bio/neurobio: Get /pub/bio/neurobio/biosim.readme (2 kb) and 
   /pub/bio/neurobio/biosim.tar.Z (2.6 MB) for the Unix version or 
   /pub/bio/neurobio/biosimpc.readme (2 kb) and 
   /pub/bio/neurobio/biosimpc.zip (150 kb) for the PC version. Contact:
   Stefan Bergdoll; Department of Software Engineering (ZXA/US); BASF Inc.;
   D-67056 Ludwigshafen; Germany; bergdoll@zxa.basf-ag.de; phone
   0621-60-21372; fax 0621-60-43735 

27. The Brain
+++++++++++++

   The Brain is an advanced neural network simulator for PCs that is simple
   enough to be used by non-technical people, yet sophisticated enough for
   serious research work. It is based upon the backpropagation learning
   algorithm. Three sample networks are included. The documentation included
   provides you with an introduction and overview of the concepts and
   applications of neural networks as well as outlining the features and
   capabilities of The Brain. The Brain requires 512K memory and MS-DOS or
   PC-DOS version 3.20 or later (versions for other OS's and machines are
   available). A 386 (with maths coprocessor) or higher is recommended for
   serious use of The Brain. Shareware payment required. Demo version is
   restricted to number of units the network can handle due to memory
   contraints on PC's. Registered version allows use of extra memory.
   External documentation included: 39Kb, 20 Pages. Source included: No
   (Source comes with registration). Available via anonymous ftp from
   ftp.tu-clausthal.de as /pub/msdos/science/brain12.zip (78 kb) and from
   ftp.technion.ac.il as /pub/contrib/dos/brain12.zip (78 kb) Contact: David
   Perkovic; DP Computing; PO Box 712; Noarlunga Center SA 5168; Australia;
   Email: dip@mod.dsto.gov.au (preferred) or dpc@mep.com or
   perkovic@cleese.apana.org.au 

28. FuNeGen 1.0
+++++++++++++++

   FuNeGen is a MLP based software program to generate fuzzy rule based
   classifiers. A limited version (maximum of 7 inputs and 3 membership
   functions for each input) for PCs is available for anonymous ftp from
   obelix.microelectronic.e-technik.th-darmstadt.de in directory 
   /pub/neurofuzzy. For further information see the file read.me. Contact:
   Saman K. Halgamuge 

29. NeuDL -- Neural-Network Description Language
++++++++++++++++++++++++++++++++++++++++++++++++

   NeuDL is a description language for the design, training, and operation
   of neural networks. It is currently limited to the backpropagation
   neural-network model; however, it offers a great deal of flexibility. For
   example, the user can explicitly specify the connections between nodes
   and can create or destroy connections dynamically as training progresses.
   NeuDL is an interpreted language resembling C or C++. It also has
   instructions dealing with training/testing set manipulation as well as
   neural network operation. A NeuDL program can be run in interpreted mode
   or it can be automatically translated into C++ which can be compiled and
   then executed. The NeuDL interpreter is written in C++ and can be easly
   extended with new instructions. NeuDL is available from the anonymous ftp
   site at The University of Alabama: cs.ua.edu (130.160.44.1) in the file 
   /pub/neudl/NeuDLver021.tar. The tarred file contains the interpreter
   source code (in C++) a user manual, a paper about NeuDL, and about 25
   sample NeuDL programs. A document demonstrating NeuDL's capabilities is
   also available from the ftp site: /pub/neudl/NeuDL/demo.doc 
   /pub/neudl/demo.doc. For more information contact the author: Joey Rogers
   (jrogers@buster.eng.ua.edu). 

30. NeoC Explorer (Pattern Maker included)
++++++++++++++++++++++++++++++++++++++++++

   The NeoC software is an implementation of Fukushima's Neocognitron neural
   network. Its purpose is to test the model and to facilitate interactivity
   for the experiments. Some substantial features: GUI, explorer and tester
   operation modes, recognition statistics, performance analysis, elements
   displaying, easy net construction. PLUS, a pattern maker utility for
   testing ANN: GUI, text file output, transformations. Available for
   anonymous FTP from OAK.Oakland.Edu (141.210.10.117) as 
   /SimTel/msdos/neurlnet/neocog10.zip (193 kB, DOS version) 

31. AINET
+++++++++

   aiNet is a shareware Neural Networks (NN) application for MS-Windows 3.1.
   It does not require learning, has no limits in parameters (input & output
   neurons), no limits in sample size. It is not sensitive toward noise in
   the data. Database can be changed dynamically. It provides a way to
   estimate the rate of error in your prediction. Missing values are handled
   automatically. It has graphical spreadsheet-like user interface and
   on-line help system. It provides also several different charts types.
   aiNet manual (90 pages) is divided into: "User's Guide", "Basics About
   Modeling with the AINET", "Examples". Special requirements: Windows 3.1,
   VGA or better. Can be downloaded from 
   ftp://ftp.cica.indiana.edu/pub/pc/win3/programr/ainet100.zip or from 
   ftp://oak.oakland.edu/SimTel/win3/math/ainet100.zip 

For some of these simulators there are user mailing lists. Get the packages
and look into their documentation for further info.

If you are using a small computer (PC, Mac, etc.) you may want to have a
look at the Central Neural System Electronic Bulletin Board (see question 
'Other sources of information'). Modem: 409-737-5312; Sysop: Wesley R.
Elsberry; 4160 Pirates' Beach, Galveston, TX, USA; welsberr@orca.tamu.edu.
There are lots of small simulator packages, the CNS ANNSIM file set. There
is an ftp mirror site for the CNS ANNSIM file set at me.uta.edu
[129.107.2.20] in the /pub/neural directory. Most ANN offerings are in 
/pub/neural/annsim. 

------------------------------------------------------------------------

Next part is part 6 (of 7). Previous part is part 4. 

-- 

Warren S. Sarle       SAS Institute Inc.   The opinions expressed here
saswss@unx.sas.com    SAS Campus Drive     are mine and not necessarily
(919) 677-8000        Cary, NC 27513, USA  those of SAS Institute.
