Subject: comp.ai.neural-nets FAQ, Part 6 of 7: Commercial software
Supersedes: <nn6.posting_825566437@hotellng.unx.sas.com>
Date: Fri, 29 Mar 1996 04:00:32 GMT

URL: ftp://ftp.sas.com/pub/neural/FAQ6.html
Maintainer: saswss@unx.sas.com (Warren S. Sarle)

This is part 6 (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
Part 2: Learning
Part 3: Information resources
Part 4: Datasets
Part 5: Free software
Part 6: Commercial software

   Commercial software packages for NN simulation?

Part 7: Hardware

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

Subject: Commercial software packages for NN
============================================
simulation?
===========

Note for future submissions: Please restrict product descriptions to a
maximum of 60 lines of 72 characters, and send an HTML-formatted version if
possible. If you include the standard header (name, company, address, etc.),
you need not count the header in the 60 line maximum.Try to make the
descriptions objective, and avoid making implicit or explicit assertions
about competing products, such as "Our product is the *only* one that does
so-and-so." The FAQ maintainer reserves the right to remove excessive
marketing hype and to edit submissions to conform to size requirements; if
he is in a good mood, he may also correct your spelling and punctuation. 

The following simulators are described below: 

1. nn/xnn 
2. BrainMaker 
3. SAS Software for Neural Networks 
4. NeuralWorks 
5. MATLAB Neural Network Toolbox 
6. Propagator 
7. NeuroForecaster 
8. Products of NESTOR, Inc. 
9. NeuroShell2/NeuroWindows 
10. NuTank 
11. Neuralyst 
12. NeuFuz4 
13. Cortex-Pro 
14. PARTEK 
15. NeuroSolutions v2.0 
16. Qnet For Windows Version 2.0 
17. NeuroLab, A Neural Network Library 
18. Neural Net Tutor for Windows 
19. havBpNet++ 
20. havFmNet++ 
21. IBM Neural Network Utility 
22. NeuroGenetic Optimizer (NGO) Version 2.0 
23. WAND 
24. Atree 3.0 Adaptive Logic Network 
25. TDL v. 1.1 (Trans-Dimensional Learning) 
26. NeurOn-Line 
27. NeuFrame, NeuroFuzzy, NeuDesk and NeuRun 
28. OWL Neural Network Library (TM) 

1. nn/xnn
+++++++++

      Name: nn/xnn
   Company: Neureka ANS
   Address: Klaus Hansens vei 31B
            5037 Solheimsviken
            NORWAY
     Phone: +47-55544163 / +47-55201548
     Email: arnemo@ii.uib.no
       URL: http://www.ii.uib.no/~arnemo/neureka/neureka.html

   Basic capabilities:

    A comprehensive system for developing and simulating artificial
    neural networks.

    nn is a high-level neural network specification language. The current
    version is best suited for feed-forward nets, but recurrent models can
    and have been implemented as well. The nn compiler can generate C code
    or executable programs, with a powerful command line interface, but
    everything may also be controlled via the graphical interface (xnn).
    It is possible for the user to write C routines that can be called from
    inside the nn specification, and to use the nn specification as a
    function that is called from a C program. These features makes nn
    well suited for application development.
    Please note that no programming is necessary in order to use the
    network models that come with the system (netpack).

    xnn is a graphical front end to networks generated by the nn compiler,
    and to the compiler itself. The xnn graphical interface is intuitive
    and easy to use for beginners, yet powerful, with many possibilities
    for visualizing network data. Data may be visualized during training,
    testing or 'off-line'.

    netpack: A number of networks have already been implemented in nn and
    can be used directly: MAdaline, ART1, Backpropagation, Counterpropagation,
    Elman, GRNN, Hopfield, Jordan, LVQ, Perceptron, RBFNN, SOFM (Kohonen).
    Several others are currently being developed.

    The pattern files used by the networks, have a simple and flexible
    format, and can easily be generated from other kinds of data. The data
    file generated by the network, can be saved in ASCII or binary format.
    Functions for converting and pre-processing data are available.

   Operating system: nn : UNIX or MS-DOS, xnn: UNIX/X-windows
                    UNIX flavours: OSF1, Solaris, AIX, IRIX

   System requirements: Min. 20 Mb HD + 4 Mb RAM available. If only the
                       nn/netpack part is used (i.e. not the GUI), much
                       less is needed.

   Approx. price: USD 2500,-
                  35% educational discount.

2. BrainMaker
+++++++++++++

           Name: BrainMaker, BrainMaker Pro
        Company: California Scientific Software
        Address: 10024 Newtown rd, Nevada City, CA, 95959 USA
      Phone,Fax: 916 478 9040, 916 478 9041
          Email:  calsci!mittmann@gvgpsa.gvg.tek.com (flakey connection)
     Basic capabilities:  train backprop neural nets
     Operating system:   DOS, Windows, Mac
     System requirements:
     Uses XMS or EMS for large models(PCs only): Pro version
     Approx. price:  $195, $795

     BrainMaker Pro 3.0 (DOS/Windows)     $795
         Gennetic Training add-on         $250
       ainMaker 3.0 (DOS/Windows/Mac)     $195
         Network Toolkit add-on           $150
     BrainMaker 2.5 Student version       (quantity sales only, about $38 each)

     BrainMaker Pro C30 Accelerator Board
               w/ 5Mb memory              $9750
               w/32Mb memory              $13,000

     Intel iNNTS NN Development System    $11,800
          Intel EMB Multi-Chip Board      $9750
          Intel 80170 chip set            $940

     Introduction To Neural Networks book $30

     California Scientific Software can be reached at:
     Phone: 916 478 9040     Fax: 916 478 9041    Tech Support: 916 478 9035
     Mail: 10024 newtown rd, Nevada City, CA, 95959, USA
     30 day money back guarantee, and unlimited free technical support.
     BrainMaker package includes:
      The book Introduction to Neural Networks
      BrainMaker Users Guide and reference manual
          300 pages, fully indexed, with tutorials, and sample networks
      Netmaker
          Netmaker makes building and training Neural Networks easy, by
          importing and automatically creating BrainMaker's Neural Network
          files.  Netmaker imports Lotus, Excel, dBase, and ASCII files.
      BrainMaker
          Full menu and dialog box interface, runs Backprop at 750,000 cps
          on a 33Mhz 486.
     ---Features ("P" means is avaliable in professional version only):
     Pull-down Menus, Dialog Boxes, Programmable Output Files,
     Editing in BrainMaker,  Network Progress Display (P),
     Fact Annotation,  supports many printers,  NetPlotter,
     Graphics Built In (P),  Dynamic Data Exchange (P),
     Binary Data Mode, Batch Use Mode (P), EMS and XMS Memory (P),
     Save Network Periodically,  Fastest Algorithms,
     512 Neurons per Layer (P: 32,000), up to 8 layers,
     Specify Parameters by Layer (P), Recurrence Networks (P),
     Prune Connections and Neurons (P),  Add Hidden Neurons In Training,
     Custom Neuron Functions,  Testing While Training,
     Stop training when...-function (P),  Heavy Weights (P),
     Hypersonic Training,  Sensitivity Analysis (P),  Neuron Sensitivity (P),
     Global Network Analysis (P),  Contour Analysis (P),
     Data Correlator (P),  Error Statistics Report,
     Print or Edit Weight Matrices,  Competitor (P), Run Time System (P),
     Chip Support for Intel, American Neurologics, Micro Devices,
     Genetic Training Option (P),  NetMaker,  NetChecker,
     Shuffle,  Data Import from Lotus, dBASE, Excel, ASCII, binary,
     Finacial Data (P),  Data Manipulation,  Cyclic Analysis (P),
     User's Guide quick start booklet,
     Introduction to Neural Networks 324 pp book

3. SAS Software for Neural Networks
+++++++++++++++++++++++++++++++++++

       Name: SAS Software

             In USA:                 In Europe:
    Company: SAS Institute, Inc.     SAS Institute, European Office 
    Address: SAS Campus Drive        Neuenheimer Landstrasse 28-30 
             Cary, NC 27513          P.O.Box 10 53 40 
             USA                     D-69043 Heidelberg 
                                     Germany
      Phone: (919) 677-8000          (49) 6221 4160
        Fax: (919) 677-4444          (49) 6221 474 850
      Email: saswss@unx.sas.com (Neural net macros)
             eurgxh@mvs.sas.com (Neural net GUI)
        URL: ftp://ftp.sas.com/pub/neural/README
   Operating systems for macros: MS Windows (3.1, 95, NT) IBM OS/2 (2.1, 3.0, Warp),
      MVS, VM/CMS, VSE/ESA, OpenVMS, ULTRIX, Digital UNIX, DG-UX, HP/UX,
      Solaris, AIX, ConvexOS, MIPS ABI, INTEL ABI, Novell UNIXware,
      Macintosh System 7.5, PowerPC 
   Operating systems for GUI: Windows 3.1, OS/2, HP/UX, Solaris, AIX
   System requirements: Lots of memory and disk space, floating point hardware
   Comments: Oriented toward data analysis and statistical applications

   Several SAS macros for feedforward neural nets are available for release
   6.08 and later. For a list of macros and articles relating to neural
   networks, see ftp://ftp.sas.com/pub/neural/README. The macros are free
   but won't do you any good unless you have licensed the required SAS
   products. If you want information about licensing SAS products, call one
   of the phone numbers listed above and ask for Software Sales. 

   There is also the SAS Neural Network Application including a graphical
   user interface, on-site training and customisation. For prices and other
   information, send email to eurgxh@mvs.sas.com or call the European
   office. 

   TNN is an elaborate system of macros for feedforward neural nets
   including multilayer perceptrons, radial basis functions, statistical
   versions of counterpropagation and learning vector quantization, a
   variety of built-in activation and error functions, multiple hidden
   layers, direct input-output connections, missing value handling,
   categorical variables, standardization of inputs and targets, and
   multiple preliminary optimizations from random initial values to avoid
   local minima. Training is done by state-of-the-art numerical optimization
   algorithms instead of tedious backprop. Maximum likelihood and
   hierarchical Bayesian training are provided for a wide range of noise
   distributions. TNN requires the SAS/OR product in release 6.08 or later.
   Release 6.10 or later is strongly recommended. Release 6.10 is required
   for the plotting macros to use SAS/INSIGHT. 

   NETIML is a collection of SAS/IML modules and macros for training and
   running multilayer perceptrons with a variety of activation and error
   functions. NETIML requires the SAS/IML product in release 6.08 or later. 

4. NeuralWorks
++++++++++++++

        Name: NeuralWorks Professional II Plus (from NeuralWare)
     Company: NeuralWare Inc.
      Adress: RIDC Park West
              202 Park West Drive
              Pittsburgh, PA 15275
       Phone: (412) 787-8222
         FAX: (412) 787-8220
       Email: sales@nware.com (soon to change to: sales@neuralware.com).
    Comments: We are also putting up a web page which should be operational
              by Christmas or shortly afterward.

    Distributor for Europe:
      Scientific Computers GmbH.
      Franzstr. 107, 52064 Aachen
      Germany
      Tel.   (49) +241-26041
      Fax.   (49) +241-44983
      Email. info@scientific.de

    Basic capabilities:
      supports over 30 different nets: backprop, art-1,kohonen,
      modular neural network, General regression, Fuzzy art-map,
      probabilistic nets, self-organizing map, lvq, boltmann,
      bsb, spr, etc...
      Extendable with optional package.
      ExplainNet, Flashcode (compiles net in .c code for runtime),
      user-defined io in c possible. ExplainNet (to eliminate
      extra inputs), pruning, savebest,graph.instruments like
      correlation, hinton diagrams, rms error graphs etc..
    Operating system   : PC,Sun,IBM RS6000,Apple Macintosh,SGI,Dec,HP.
    System requirements: varies. PC:2MB extended memory+6MB Harddisk space.
                         Uses windows compatible memory driver (extended).
                         Uses extended memory.
    Approx. price      : call (depends on platform)
    Comments           : award winning documentation, one of the market
                         leaders in NN software.

5. MATLAB Neural Network Toolbox
++++++++++++++++++++++++++++++++

      Contact: The MathWorks, Inc.     Phone: 508-653-1415
               24 Prime Park Way       FAX: 508-653-2997
               Natick, MA 01760 email: info@mathworks.com

   The Neural Network Toolbox is a powerful collection of MATLAB functions
   for the design, training, and simulation of neural networks. It supports
   a wide range of network architectures with an unlimited number of
   processing elements and interconnections (up to operating system
   constraints). Supported architectures and training methods include:
   supervised training of feedforward networks using the perceptron learning
   rule, Widrow-Hoff rule, several variations on backpropagation (including
   the fast Levenberg-Marquardt algorithm), and radial basis networks;
   supervised training of recurrent Elman networks; unsupervised training of
   associative networks including competitive and feature map layers;
   Kohonen networks, self-organizing maps, and learning vector quantization.
   The Neural Network Toolbox contains a textbook-quality Users' Guide, uses
   tutorials, reference materials and sample applications with code examples
   to explain the design and use of each network architecture and paradigm.
   The Toolbox is delivered as MATLAB M-files, enabling users to see the
   algorithms and implementations, as well as to make changes or create new
   functions to address a specific application.

   (Comment from Nigel Dodd, nd@neural.win-uk.net): there is also a free
   Neural Network Based System Identification Toolbox available from 
   http://kalman.iau.dtu.dk/Projects/proj/nnsysid.html that contains many of
   the supervised training algorithms, some of which are duplicated in C
   code which should run faster. This free toolbox does regularisation and
   pruning which the costly one doesn't attempt (as of Nov 1995). 

   (Message from Eric A. Wan, ericwan@eeap.ogi.edu) FIR/TDNN Toolbox for
   MATLAB: Beta version of a toolbox for FIR (Finite Impulse Response) and
   TD (Time Delay) Neural Networks. For efficient stochastic implementation,
   algorithms are written as MEX compatible c-code which can be called as
   primitive functions from within MATLAB. Both source and compiled
   functions are available. URL: http://www.eeap.ogi.edu/~ericwan/fir.html

6. Propagator
+++++++++++++

     Contact: ARD Corporation,
              9151 Rumsey Road, Columbia, MD  21045, USA
              propagator@ard.com
     Easy to use neural network training package.  A GUI implementation of
     backpropagation networks with five layers (32,000 nodes per layer).
     Features dynamic performance graphs, training with a validation set,
     and C/C++ source code generation.
     For Sun (Solaris 1.x & 2.x, $499),
         PC  (Windows 3.x, $199)
         Mac (System 7.x, $199)
     Floating point coprocessor required, Educational Discount,
     Money Back Guarantee, Muliti User Discount
     See http://www.cs.umbc.edu/~zwa/Gator/Description.html
     Windows Demo on:
       nic.funet.fi        /pub/msdos/windows/demo
       oak.oakland.edu     /pub/msdos/neural_nets
           gatordem.zip    pkzip 2.04g archive file
           gatordem.txt    readme text file

7. NeuroForecaster & VisuaData
++++++++++++++++++++++++++++++

   Name: NeuroForecaster(TM)/Genetica 4.1a
   Contact: Accel Infotech (S) Pte Ltd; 648 Geylang Road; Republic of
   Singapore 1438; 
   Phone: +65-7446863, 3366997; Fax: +65-3362833, Internet:
   accel@technet.sg, accel@singapore.com

   Neuroforecaster 4.1a for Windows is priced at US$1199 per single user
   license. Please email us (accel@technet.sg) for order form. 

   For more information and evaluation copy please visit 
   http://www.singapore.com/products/nfga. 
   NeuroForecaster is a user-friendly ms-windows neural network program
   specifically designed for building sophisticated and powerful forecasting
   and decision-support systems (Time-Series Forecasting, Cross-Sectional
   Classification, Indicator Analysis) 
      Features: 
    o GENETICA Net Builder Option for automatic network optimization 
    o 12 Neuro-Fuzzy Network Models 
    o Multitasking & Background Training Mode 
    o Unlimited Network Capacity 
    o Rescaled Range Analysis & Hurst Exponent to Unveil Hidden Market 
    o Cycles & Check for Predictability 
    o Correlation Analysis to Compute Correlation Factors to Analyze the 
    o Significance of Indicators 
    o Weight Histogram to Monitor the Progress of Learning 
    o Accumulated Error Analysis to Analyze the Strength of Input Indicators
      The following example applications are included in the package:
    o Credit Rating - for generating the credit rating of bank loan
      applications. 
    o Stock market 6 monthly returns forecast 
    o Stock selection based on company ratios 
    o US$ to Deutschmark exchange rate forecast 
    o US$ to Yen exchange rate forecast 
    o US$ to SGD exchange rate forecast 
    o Property price valuation 
    o Chaos - Prediction of Mackey-Glass chaotic time series 
    o SineWave - For demonstrating the power of Rescaled Range Analysis and
      significance of window size 
      Techniques Implemented: 
    o GENETICA Net Builder Option - network creation & optimization based on
      Darwinian evolution theory 
    o Backprop Neural Networks - the most widely-used training algorithm 
    o Fastprop Neural Networks - speeds up training of large problems 
    o Radial Basis Function Networks - best for pattern classification
      problems 
    o Neuro-Fuzzy Network 
    o Rescaled Range Analysis - computes Hurst exponents to unveil hidden
      cycles & check for predictability 
    o Correlation Analysis - to identify significant input indicators 
    o Companion Software - VisuaData for Windows A user-friendly data
   management program designed for intelligent technical analysis. It reads 
   -------------------------------------------------------------------------
   MetaStock, CSI, Computrac and various ASCII data file formats
   directly, generates over 100 popular and new technical indicators and
   buy/sell signals. 

8. Products of NESTOR, Inc.
+++++++++++++++++++++++++++

   530 Fifth Avenue;
   New York, NY 10036; USA;
   Tel.: 001-212-398-7955

   Founders:
   Dr. Leon Cooper (having a Nobel Price) and Dr. Charles Elbaum
   (Brown University).

   Neural Network Models:
   Adaptive shape and pattern recognition (Restricted Coulomb Energy - RCE)
   developed by NESTOR is one of the most powerfull Neural Network Model
   used in a later products.

   The basis for NESTOR products is the Nestor Learning System - NLS. Later
   are developed: Character Learning System - CLS and Image Learning System
   - ILS.  Nestor Development System - NDS is a development tool in
   Standard C - a powerfull PC-Tool for simulation and development of
   Neural Networks.

   NLS is a multi-layer, feed forward system with low connectivity within
   each layer and no relaxation procedure used for determining an output
   response.  This unique architecture allows the NLS to operate in real
   time without the need for special computers or custom hardware.

   NLS is composed of multiple neural networks, each specializing in a
   subset of information about the input patterns. The NLS integrates the
   responses of its several parallel networks to produce a system response.

   Minimized connectivity within each layer results in rapid training and
   efficient memory utilization- ideal for current VLSI technology. Intel
   has made such a chip - NE1000.


9. NeuroShell2/NeuroWindows
+++++++++++++++++++++++++++

   NeuroShell 2 combines powerful neural network architectures, a Windows
   icon driven user interface, and sophisticated utilities for MS-Windows
   machines. Internal format is spreadsheet, and users can specify that
   NeuroShell 2 use their own spreadsheet when editing. Includes both
   Beginner's and Advanced systems, a Runtime capability, and a choice of 15
   Backpropagation, Kohonen, PNN and GRNN architectures. Includes Rules,
   Symbol Translate, Graphics, File Import/Export modules (including
   MetaStock from Equis International) and NET-PERFECT to prevent
   overtraining. Options available: Market Technical Indicator Option
   ($295), Market Technical Indicator Option with Optimizer ($590), and Race
   Handicapping Option ($149). NeuroShell price: $495.

   NeuroWindows is a programmer's tool in a Dynamic Link Library (DLL) that
   can create as many as 128 interactive nets in an application, each with
   32 slabs in a single network, and 32K neurons in a slab. Includes
   Backpropagation, Kohonen, PNN, and GRNN paradigms. NeuroWindows can mix
   supervised and unsupervised nets. The DLL may be called from Visual
   Basic, Visual C, Access Basic, C, Pascal, and VBA/Excel 5. NeuroWindows
   price: $369.

   GeneHunter is a genetic algorithm with a Dynamic Link Library of genetic
   algorithm functions that may be called from programming languages such as
   Visual Basicd or C. For non-programmers, GeneHunter also includes an
   Exceld Add-in program which allows the user to solve an optimization
   problem from an Excel spreadsheet. 

   Contact:
   Ward Systems Group, Inc.;
   Executive Park West;
   5 Hillcrest Drive;
   Frederick, MD 21702;
   USA;
   Phone: 301 662-7950; FAX: 301 662-5666.
   email: WardSystems@msn.com
   URL: http://www.wardsystems.com
   Contact us for a free demo diskette and Consumer's Guide to Neural
   Networks. 

10. NuTank
++++++++++

   NuTank stands for NeuralTank. It is educational and entertainment
   software. In this program one is given the shell of a 2 dimentional
   robotic tank. The tank has various I/O devices like wheels, whiskers,
   optical sensors, smell, fuel level, sound and such. These I/O sensors are
   connected to Neurons. The player/designer uses more Neurons to
   interconnect the I/O devices. One can have any level of complexity
   desired (memory limited) and do subsumptive designs. More complex design
   take slightly more fuel, so life is not free. All movement costs fuel
   too. One can also tag neuron connections as "adaptable" that adapt their
   weights in acordance with the target neuron. This allows neurons to
   learn. The Neuron editor can handle 3 dimention arrays of neurons as
   single entities with very flexible interconect patterns.

   One can then design a scenario with walls, rocks, lights, fat (fuel)
   sources (that can be smelled) and many other such things. Robot tanks are
   then introduced into the Scenario and allowed interact or battle it out.
   The last one alive wins, or maybe one just watches the motion of the
   robots for fun. While the scenario is running it can be stopped, edited,
   zoom'd, and can track on any robot.

   The entire program is mouse and graphicly based. It uses DOS and VGA and
   is written in TurboC++. There will also be the ability to download
   designs to another computer and source code will be available for the
   core neural simulator. This will allow one to design neural systems and
   download them to real robots. The design tools can handle three
   dimentional networks so will work with video camera inputs and such.
   Eventualy I expect to do a port to UNIX and multi thread the sign. I also
   expect to do a Mac port and maybe NT or OS/2

   Copies of NuTank cost $50 each. Contact: Richard Keene; Keene Educational
   Software; Dick.Keene@Central.Sun.COM

   NuTank shareware with the Save options disabled is available via
   anonymous ftp from the Internet, see the file /pub/incoming/nutank.readme
   on the host cher.media.mit.edu. 

11. Neuralyst
+++++++++++++

   Name:  Neuralyst Version 1.4;
   Company:  Cheshire Engineering Corporation;
   Address:  650 Sierra Madre Villa, Suite 201, Pasedena CA 91107;
   Phone:    818-351-0209;
   Fax:      818-351-8645;

   Basic capabilities: training of backpropogation neural nets. Operating
   system: Windows or Macintosh running Microsoft Excel Spreadsheet.
   Neuralyst is an add-in package for Excel. Approx. price: $195 for windows
   or Mac. 

12. NeuFuz4
+++++++++++

         Name: NeuFuz4
      Company: National Semiconductor Corporation
      Address: 2900 Semiconductor Drive, Santa Clara, CA, 95052,
           or: Industriestrasse 10, D-8080 Fuerstenfeldbruck, Germany,
           or: Sumitomo Chemical Engineering Center, Bldg. 7F 1-7-1, Nakase,
                 Mihama-Ku, Chiba-City, Ciba Prefecture 261, JAPAN,
           or: 15th Floor, Straight Block, Ocean Centre, 5 Canton Road, Tsim
                 Sha Tsui East, Kowloon, Hong Kong,
        Phone: (800) 272-9959    (Americas),
             : 011-49-8141-103-0 Germany
             : 0l1-81-3-3299-7001 Japan
             : (852) 737-1600 Hong Kong
        Email: neufuz@esd.nsc.com (Neural net inquiries only)
          URL: http://www.commerce.net/directories/participants/ns/home.html

   Basic capabilities:
     Uses backpropagation techniques to initially select fuzzy rules
     and membership functions. The result is a fuzzy associative memory (FAM)
     which implements an approximation of the training data.
   Operating Systems: 486DX-25 or higher with math co-processor
                      DOS 5.0 or higher  with Windows 3.1, mouse,
                      VGA or better, minimum 4 MB RAM, and parallel port.
   Approx. price    : depends on version - see below.
   Comments         :
      Not for the serious Neural Network researcher, but good for a person
      who has little understanding of Neural Nets - and wants to keep it that
      way. The systems are aimed at low end controls applications in
      automotive, industrial, and appliance areas.  NeuFuz is a neural-fuzzy
      technology which uses backpropagation techniques to initially select
      fuzzy rules and membership functions.  Initial stages of design using
      NeuFuz technology are performed using training data and
      backpropagation. The result is a fuzzy associative memory (FAM) which
      implements an approximation of the training data.  By implementing a
      FAM, rather than a multi-layer perceptron, the designer has a solution
      which can be understood and tuned to a particular application using
      Fuzzy Logic design techniques.
      There are several different versions, some with COP8 Code Generator
      (COP8 is National's family of 8-bit microcontrollers) and
      COP8 in-circuit emulator (debug module).

13. Cortex-Pro
++++++++++++++

   Cortex-Pro information is on WWW at: 
   http://www.neuronet.ph.kcl.ac.uk/neuronet/software/cortex/www1.html.
   You can download a working demo from there.
   Contact: Michael Reiss ( http://www.mth.kcl.ac.uk/~mreiss/mick.html)
   email: <m.reiss@kcl.ac.uk>. 

14. PARTEK
++++++++++

   PARTEK is a powerful, integrated environment for visual and quantitative
   data analysis and pattern recognition. Drawing from a wide variety of
   disciplines including Artificial Neural Networks, Fuzzy Logic, Genetic
   Algorithms, and Statistics, PARTEK integrates data analysis and modeling
   tools into an easy to use "point and click" system. The following modules
   are available from PARTEK; functions from different modules are
   integrated with each other whereever possible: 
   1. The PARTEK/AVB - The Analytical/Visual Base. (TM) 

       * Analytical Spreadsheet (TM)
         The Analytical Spreadsheet is a powerful and easy to use data analysis,
         transformations, and visualization tool.  Some features include:
            - import native format ascii/binary data
            - recognition and resolution of missing data
            - complete set of common mathematical & statistical functions
            - contingency table analysis / correspondence analysis
            - univariate histogram analysis
            - extensive set of smoothing and normalization transformations
            - easily and quickly plot color-coded 1-D curves and histograms,
              2-D, 3-D, and N-D mapped scatterplots, highlighting selected
              patterns
            - Command Line (Tcl) and Graphical Interface

       * Pattern Visualization System (TM)
         The Pattern Visualization System offers powerful tools for
         visual analysis of the patterns in your data.  Some features include:
            - automatically maps N-D data down to 3-D for visualization of
              *all* of your variables at once
            - hard copy color Postscript output
            - a variety of color-coding, highlighting, and labeling options
              allow you to generate meaningful graphics

       * Data Filters
         Filter out selected rows and/or columns of your data for flexible and
         efficient cross-validation, jackknifing, bootstrapping, feature set
         evaluation, and more.

       * Random # Generators
         Generate random numbers from any of the following parameterized
         distributions:
            - uniform, normal, exponential, gamma, binomial, poisson

       * Many distance/similarity metrics
         Choose the appropriate distance metric for your data:
            - euclidean, mahalanobis, minkowski, maximum value, absolute value,
              shape coefficient, cosine coefficient, pearson correlation,
              rank correlation, kendall's tau, canberra, and bray-curtis

       * Tcl/Tk command line interface

   2. The PARTEK/DSA - Data Structure Analysis Module 

       * Principal Components Analysis and Regression
         Also known as Eigenvector Projection or Karhunen-Loeve Expansions,
         PCA removes redundant information from your data.
            - component analysis, correlate PC's with original variables
            - choice of covariance, correlation, or product dispersion matrices
            - choice of eigenvector, y-score, and z-score projections
            - view SCREE and log-eigenvalue plots

       * Cluster Analysis
         Does the data form groups?  How many?  How compact?  Cluster Analysis
         is the tool to answer these questions.
            - choose between several distance metrics
            - optionally weight individual patterns
            - manually or auto-select the cluster number and initial centers
            - dump cluster counts, mean, cluster to cluster distances,
              cluster variances, and cluster labeled data to a matrix viewer or
              the Analytical Spreadsheet for further analysis
            - visualize n-dimensional clustering
            - assess goodness of partion using several internal and external
              criteria metrics

       * N-Dimensional Histogram Analysis
         Among the most inportant questions a researcher needs to know when
         analyzing patterns is whether or not the patterns can distinguish
         different classes of data.  N-D Histogram Analysis is one tool to
         answer this question.
            - measures histogram overlap in n-dimensional space
            - automatically find the best subset of features
            - rank the overlap of your best feature combinations

       * Non-Linear Mapping
         NLM is an iterative algorithm for visually analyzing the structure of
         n-dimensional data.  NLM produces a non-linear mapping of data which
         preserves interpoint distances of n-dimensional data while reducing
         to a lower dimensionality - thus preserving the structure of the data.
            - visually analyze structure of n-dimensional data
            - track progress with error curves
            - orthogonal, PCA, and random initialization

   3. The PARTEK/CP - Classification and Prediction Module 

       * Multi-Layer Perceptron
         The most popular among the neural pattern recognition tools is the MLP.
         PARTEK takes the MLP to a new dimension, by allowing the network to
         learn by adapting ALL of its parameters to solve a problem.
            - adapts output bias, neuron activation steepness, and neuron
              dynamic range, as well as weights and input biases
            - auto-scaling at input and output - no need to rescale your data
            - choose between sigmoid, gaussian, linear, or mixture of neurons
            - learning rate, momentum can be set independently for each parameter
            - variety of learning methods and network initializations
            - view color-coded network, error, etc as network trains, tests, runs

       * Learning Vector Quantization
         Because LVQ is a multiple prototype classifier, it adapts to identify
         multiple sub-groups within classes
            - LVQ1, LVQ2, and LVQ3 training methods
            - 3 different functions for adapting learning rate
            - choose between several distance metrics
            - fuzzy and crisp classifications
            - set number of prototypes individually for each class

       * Bayesian Classifier
         Bayes methods are the statistical decision theory approach to
         classification.  This classifier uses statistical properties of your
         data to develop a classification model.

   PARTEK is available on HP, IBM, Silicon Graphics, and SUN workstations.
   For more information, send email to "info@partek.com" or call
   (314)926-2329. 

15. NeuroSolutions v2.0
+++++++++++++++++++++++

   NeuroSolutions is a graphical neural network simulation tool. It
   supports trajectory learning with backpropagation through time.
   Because of its object-oriented design, NeuroSolutions provides the
   flexibility needed to construct a wide range of learning paradigms
   and network topologies.  Its GUI and extensive probing ability
   streamline the experimentation process by providing real-time
   analysis of the network during learning.

   Construct any neural network belonging to the additive model,
   including locally and globally recurrent systems.  Use a variety of
   unsupervised learning procedures, such as Hebbian, Sanger's, Oja's,
   Competitive and Kohonen.  Implement RBF, PCA, counterpropagation and
   other hybrid network topologies by seamlessly integrating
   supervised and unsupervised learning.

   During learning, animate changes of internal variables such as
   activations, weights, sensitivities and gradients with a variety of
   probes.  Examples are the oscilloscope, spectrum analyzer, 3D state
   space, scatter, 3D surface, matrix and bitmap.

   NeuroSolutions'  NeuralWizard utility automates the neural network
   design process.  Choose between a wide range of neural models. The
   network parameters are dynamically adjusted based on the user's
   training data.  It is a powerful tool used by both beginners and
   researchers alike.

   NeuroSolutions offers advanced features to meet the integration
   needs of neural network developers.  Once a system is designed and
   simulated using the icon-based development environment,
   NeuroSolutions will generate ANSI-compatible C++ source code to be
   compiled and linked into custom applications.  NeuroSolutions can
   also be customized through user-defined DLL's and OLE support.

   Price: $195 - $1995

   Demo copy available from company or by anonymous ftp:
           ftp://oak.oakland.edu/SimTel/win3/neurlnet/ns2demo1.zip
           ftp://oak.oakland.edu/SimTel/win3/neurlnet/ns2demo2.zip

           NeuroDimension, Inc.
           720 S.W. 2nd Ave., Suite 458
           Gainesville FL, 32601
   Phone:  (800) 634-3327 or
           (904) 377-5144
   FAX:    (904) 338-6779
   Email:  info@nd.com
   URL:    http://www.nd.com/

16. Qnet For Windows Version 2.0
++++++++++++++++++++++++++++++++

   Vesta Services, Inc.
   1001 Green Bay Rd, Suite 196
   Winnetka, IL   60093
   Phone:   (708) 446-1655
   E-Mail:  VestaServ@aol.com

   Trial Version Available: 
   ftp://oak.oakland.edu/SimTel/win3/neurlnet/qnetv2t.zip 

   Vesta Services announces Qnet for Windows Version 2.0. Qnet is an
   advanced neural network modeling system that is ideal for developing and
   implementing neural network solutions under Windows. The use of neural
   network technology has grown rapidly over the past few years and is being
   employed by an increasing number of disciplines to automate complex
   decision making and problem solving tasks. Qnet Version 2 is a powerful,
   32-bit, neural network development system for Windows NT, Windows 95 and
   Windows 3.1/Win32s. In addition its development features, Qnet automates
   access and use of Qnet neural networks under Windows. 

   Qnet neural networks have been successfully deployed to provide solutions
   in finance, investing, marketing, science, engineering, medicine,
   manufacturing, visual recognition... Qnet's 32-bit architecture and
   high-speed training engine tackle problems of large scope and size. Qnet
   also makes accessing this advanced technology easy. Qnet's neural network
   setup dialogs guide users through the design process. Simple copy/paste
   procedures can be used to transfer training data from other applications
   directly to Qnet. Complete, interactive analysis is available during
   training. Graphs monitor all key training information. Statistical checks
   measure model quality. Automated testing is available for training
   optimization. To implement trained neural networks, Qnet offers a variety
   of choices. Qnet's built-in recall mode can process new cases through
   trained neural networks. Qnet also includes a utility to automate access
   and retrieval of solutions from other Windows applications. All popular
   Windows spreadsheet and database applications can be setup to retrieve
   Qnet solutions with the click of a button. Application developers are
   provided with DLL access to Qnet neural networks and for complete
   portability, ANSI C libraries are included to allow access from virtually
   any platform. 

   Qnet for Windows is being offered at an introductory price of $199. It is
   available immediately and may be purchased directly from Vesta Services.
   Vesta Services may be reached at (voice) (708) 446-1655; (FAX) (708)
   446-1674; (e-mail) VestaServ@aol.com; (mail) 1001 Green Bay Rd, #196,
   Winnetka, IL 60093 

17. NeuroLab, A Neural Network Library
++++++++++++++++++++++++++++++++++++++

   Contact: Mikuni Berkeley R & D Corporation; 4000 Lakeside Dr.; Richmond,
   CA
   Tel: 510-222-9880; Fax: 510-222-9884; e-mail: neurolab-info@mikuni.com 

   NeuroLab is a block-diagram-based neural network library for Extend
   simulation software (developed by Imagine That, Inc.). The library aids
   the understanding, designing and simulating of neural network systems.
   The library consists of more than 70 functional blocks for artificial
   neural network implementation and many example models in several
   professional fields.The package provides icon-based functional blocks for
   easy implementation of simulation models. Users click, drag and connect
   blocks to construct a neural network and can specify network
   parameters--such as back propagation methods, learning rates, initial
   weights, and biases--in the dialog boxes of the functional blocks.
   Users can modify blocks with the Extend model-simulation scripting
   language, ModL, and can include compiled program modules written in other
   languages using XCMD and XFCN (external command and external function)
   interfaces and DLL (dynamic linking library) for Windows. The package
   provides many kinds of output blocks to monitor neural network status in
   real time using color displays and animation and includes special blocks
   for control application fields. Educational blocks are also included for
   people who are just beginning to learn about neural networks and their
   applications.
   The library features various types of neural networks --including
   Hopfield, competitive, recurrent, Boltzmann machine, single/multilayer
   feed-forward, perceptron, context, feature map, and counter-propagation--
   and has several back-propagation options: momentum and normalized
   methods, adaptive learning rate, and accumulated learning.

   The package runs on Macintosh II or higher (FPU recommended) with system
   6.0.7 or later and PC compatibles (486 or higher recommended) with
   Windows 3.1 or later, and requires 4Mbytes of RAM. Models are
   transferable between the two platforms. NeuroLab v1.2 costs US$495
   (US$999 bundled with Extend v3.1). Educational and volume discounts are
   available.
   A free demo can be downloaded by ftp://ftp.mikuni.com/pub/neurolab or 
   http://www.mikuni.com/. Orders, questions or suggestions can be sent by
   e-mail to neurolab-info@mikuni.com. 

18. Neural Net Tutor for Windows
++++++++++++++++++++++++++++++++

   Neural networks are great! If trained properly, they can learn to predict
   all sorts of things (stock behavior, who's going to win the superbowl,
   that kind of stuff). But they're difficult to get a handle on, when
   you're first approaching the subject. Well, having said that, you just
   know that we're going to say that we've done away with that impediment.

   Neural Net Tutor (see 
   http://mmink.cts.com:80/mmink/dossiers/attg/nntutor.html is a bit unusual
   is that it's both a standalone (backprop) neural engine (a very graphical
   one, I might add), and a complete hypertext course wrapped into a single
   package. The course is based on an actual university-level offering, and
   takes a couple of days to work through. When you're done, you'll have a
   very good idea what neural nets are, how they work, and how to use them
   -- and, for your convenience, you also have an engine to apply all that
   new-found knowledge towards.

   Neural Net Tutor costs just 70 bucks! For that, you get the
   course/engine, a complete set of supporting lab notes, and even, if you
   can believe this, a high-quality T shirt bearing our company logo: an
   artificial brain (and our "Get a Brain" slogan). What's the catch?
   Nothing. In fact, we're so sure that you'll think it was money well
   spent, that if, after working with it for a while, you decide it wasn't
   worth it, send it back. We'll refund your money, and you keep the T! 

19. havBpNet++
++++++++++++++

   havBpNet++ is a C++ class library that implements feedforward, simple
   recurrent and random-ordered recurrent nets trained by backpropagation.
   Used for both stand-alone and embedded network training and consultation
   applications. A simple layer-based API, along with no restrictions on
   layer-size or number of layers, makes it easy to build standard 3-layer
   nets or much more complex multiple sub-net topologies. 

   Supports all standard network parameters (learning-rate, momentum,
   Cascade- coefficient, weight-decay, batch training, etc.). Includes 5
   activation-functions (Linear, Logistic-sigmoid, Hyperbolic-tangent, Sin
   and Hermite) and 3 error-functions (e^2, e^3, e^4). Also included is a
   special scaling utility for data with large dynamic range. 

   Several data-handling classes are also included. These classes, while not
   required, may be used to provide convenient containers for training and
   consultation data. They also provide several
   normalization/de-normalization methods. 

   havBpNet++ is delivered as fully documented source + 200 pg
   User/Developer Manual. Includes a special DLL version. Includes several
   example trainers and consulters with data sets. Also included is a fully
   functioning copy of the havBpETT demo (with network-save enabled). 

   NOTE: a freeware version (Save disabled) of the havBpETT demo may be
   downloaded from the hav.Software home-page: http://www.neosoft.com/~hav
   or by anonymous ftp from 
   ftp://ftp.neosoft.com/pub/users/h/hav/havBpETT/demo2.exe. 

   Platforms:      Tested platforms include - PC (DOS, Windows-3.1, NT, Unix),
                   HP (HPux), SUN (Sun/OS), IBM (AIX), SGI (Irix).
                   Source and Network-save files portable across platforms.

   Licensing:      havBpNet++ is licensed by number of developers.
                   A license may be used to support development on any number
                   and types of cpu's.
                   No Royalties or other fees (except for OEM/Reseller)

   Price:          Individual        $50.00 - one developer
                   Site             $500.00 - multiple developers - one location
                   Corporate       $1000.00 - multiple developers and locations
                   OEM/Reseller    quoted individually
                   (by American Express, bank draft and approved company PO)

   Media:  3.5-inch floppy - ascii format (except havBpETT which is in PC-exe
                                           format).
                   hav.Software
                   P.O. Box 354
                   Richmond, Tx.  77406-0354 - USA
   Phone:  (713) 341-5035
   Email:  hav@neosoft.com
   Web:    http://www.neosoft.com/~hav

20. havFmNet++
++++++++++++++

   havFmNet++ is a C++ class library that implements Self-Organizing Feature
   Map nets. Map-layers may be from 1 to any dimension. 

   havFmNet++ may be used for both stand-alone and embedded network training
   and consultation applications. A simple Layer-based API, along with no
   restrictions on layer-size or number of layers, makes it easy to build
   single- layer nets or much more complex multiple-layer topologies.
   havFmNet++ is fully compatible with havBpNet++ which may be used for pre-
   and post- processing. 

   Supports all standard network parameters (learning-rate, momentum,
   neighborhood, conscience, batch, etc.). Uses On-Center-Off-Surround
   training controlled by a sombrero form of Kohonen's algorithm. Updates
   are controllable by three neighborhood related parameters:
   neighborhood-size, block-size and neighborhood-coefficient cutoff. Also
   included is a special scaling utility for data with large dynamic range. 

   Several data-handling classes are also included. These classes, while
   not required, may be used to provide convenient containers for training
   and consultation data. They also provide several
   normalization/de-normalization methods. 

   havFmNet++ is delivered as fully documented source plus 200 pg
   User/Developer Manual. Includes several example trainers and consulters
   with data sets. 

   Platforms:      Tested platforms include - PC (DOS, Windows-3.1, NT, Unix),
                   HP (HPux), SUN (Sun/OS), IBM (AIX), SGI (Irix).
                   Source and Network-save files portable across platforms.

   Licensing:      havFmNet++ is licensed by number of developers.
                   A license may be used
                   to support development on any number and types of cpu's.
                   No Royalties or other fees (possible exception for OEM).

   Price:          Individual        $50.00 - one developer
                   Site             $500.00 - multiple developers - one location
                   Corporate       $1000.00 - multiple developers and locations
                   OEM/Reseller    quoted individually
                   (by American Express, bank draft and approved company PO)

   Media:  3.5-inch floppy - ascii format

                   hav.Software
                   P.O. Box 354
                   Richmond, Tx.  77406-0354 - USA
   Phone:  (713) 341-5035
   Email:  hav@neosoft.com
   Web:    http://www.neosoft.com/~hav

21. IBM Neural Network Utility
++++++++++++++++++++++++++++++

   Product Name: IBM Neural Network Utility
   Distributor: Contact a local reseller or call 1-800-IBM-CALL, Dept. SA045
   to order.
   Basic capabilities: The Neural Network Utility Family consists of six
   products: client/server capable versions for OS/2, Windows, AIX, and
   standalone versions for OS/2 and Windows. Applications built with NNU are
   portable to any of the supported platforms regardless of the development
   platform. NNU provides a powerful, easy to use, point-and-click graphical
   development environment. Features include: data translation and scaling,
   applicaton generation, multiple network models, and automated network
   training. We also support fuzzy rule systems, which can be combined with
   the neural networks. Once trained, our APIs allow you to embed your
   network and/or rulebase into your own applications.
   Operating Systems: OS/2, Windows, AIX, AS/400
   System requirements: basic; request brochure for more details
   Price: Prices start at $250
   For product brochures, detailed pricing information, or any other
   information, send a note to nninfo@vnet.ibm.com. 

22. NeuroGenetic Optimizer (NGO) Version 2.0
++++++++++++++++++++++++++++++++++++++++++++

   BioComp's leading product is the NeuroGenetic Optimizer, or NGO.  As 
   the name suggests, the NGO is a neural network development tool that 
   uses genetic algorithms to optimize the inputs and structure of a neural 
   network. Without the NGO, building neural networks can be tedious and 
   time consuming even for an expert.  For example, in a relatively simple 
   neural network, the number of possible combination of inputs and neural 
   network structures can be easily over 100 billion.  The difference 
   between an average network and an optimum network is substantial.  The 
   NGO searches for optimal neural network solutions. See our web page at 
   http://www.bio-comp.com. for a demo that you can download and try out.  
   Our customers who have used other neural network development tools are 
   delighted with both the ease of use of the NGO and the quality to their 
   results.

   BioComp Systems, Inc. introduced version 1.0 of the NGO in January of 
   1995 and now proudly announces version 2.0.  With version 2.0, the NGO 
   is now equipped for predicting time-based information such as product 
   sales, financial markets and instruments, process faults, etc., in 
   addition to its current capabilities in functional modeling, 
   classification, and diagnosis.

   While the NGO embodies sophisticated genetic algorithm search and neural 
   network modeling technology, it has a very easy to use GUI interface for 
   Microsoft Windows.  You don't have to know or understand the underlying 
   technology to build highly effective financial models.  On the other 
   hand, if you like to work with the technology, the NGO is highly 
   configurable to customize the NGO to your liking.

   Key new features of the NGO include:
   * Highly effective "Continuous Adaptive Time", Time Delay and lagged 
   input Back Propagation neural networks with optional recurrent outputs, 
   automatically competing and selected based on predictive accuracy.
   * Walk Forward Train/Test/Validation model evaluation for assuring model 
   robustness,
   * Easy input data lagging for Back Propagation neural models,
   * Neural transfer functions and techniques that assure proper 
   extrapolation of predicted variables to new highs,
   * Confusion matrix viewing of Predicted vs. Desired results,
   * Exportation of models to Excel 5.0 (Win 3.1) or Excel 7.0 (Win'95/NT) 
   through an optional Excel Add-In
   * Five accuracies to choose from including; Relative Accuracy, 
   R-Squared, Mean Squared Error (MSE), Root Mean Square (RMS) Error and 
   Average Absolute error.

   With version 2.0, the NGO is now available as a full 32 bit application 
   for Windows '95 and Windows NT to take advantage of the 32 bit 
   preemptive multitasking power of those platforms. A 16 bit version for 
   Windows 3.1 is also available.  Customized professional server based 
   systems are also available for high volume automated model generation 
   and prediction. Prices start at $195.

   BioComp Systems, Inc.
   Overlake Business Center
   2871 152nd Avenue N.E.
   Redmond, WA 98052, USA
   1-800-716-6770 (US/Canada voice)=20  1-206-869-6770 (Local/Int'l voice)
   1-206-869-6850 (Fax)                 http://www.bio-comp.com.
   biocomp@biocomp.seanet.com           70673.1554@compuserve.com

23. WAND
++++++++

   Weightless Neural Design system for Education and Industry. 
   Developed by Novel Technical Solutions in association with Imperial
   College of Science, Technology and Medicine (London UK). 
   WAND introduces Weightless Neural Technology as applied to Image
   Recognition. 
   It includes an automated image preparation package, a weightless neural
   simulator and a comprehensive manual with hands-on tutorials. 
   Full information including a download demo can be obtained from: 
   http://www.neuronet.ph.kcl.ac.uk/neuronet/software/nts/neural.html 
   To contact Novel Technical Solutions email: <neural@nts.sonnet.co.uk>. 

24. Atree 3.0 Adaptive Logic Network Development System (for
++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++
   Windows)
   ++++++++

   Contact:
   Dendronic Decisions Limited
   3624 - 108 Street
   Edmonton, Alberta
   Canada T6J 1B4

   tel/fax +1 (403) 438-8285
   or email William W. Armstrong, President (arms@cs.ualberta.ca)
   or use the Dendronic forum on CompuServe (GO DENDRONIC)

   Atree 3.0 trains feedforward networks having perceptrons in
   the first hidden layer and logic gates AND and OR in other hidden
   layers.  Functions from real inputs to a real output can be represented.

   Users can specify constraints on monotonicity, derivatives (slopes)
   and convexity of functions being learned.  Such expert knowledge
   can be used to ensure the result of training satisfies requirements
   of known physical or economic laws.  Functions can be inverted without
   additional training, a capability useful in control applications.

   The execution library, which computes learned functions at high
   speed, is offered in source form (code suitable for Windows and
   Unix is available free of charge).  Atree 3.0 outputs ALN decision
   trees in human-readable form (for checking) as well as in binary form
   (for fast reloading).  The commercial license allows redistribution
   and modification of execution code.

   Atree 3.0 may be used for data analysis, prediction, pattern recognition
   and for real-time control applications that must run on a typical computer
   (such as a PC).  Scripts can be run automatically and can be called from
   macros in Microsoft Excel and MS Access or from other applications.
   Many samples showing how to use Atree 3.0 are provided.

   The open architecture of the execution library is important
   when outputs have to be checked for conformity to a specification.
   The user is entirely responsible for making his/her applications
   safe to use, of course, but the openness of everything concerned with
   execution of the results of Atree 3.0 training supports that goal.

   A manual of approximately 100 pages will be supplied.

   Introductory price until March 31,1996: $99 US (or $125 Canadian
   for Canadian residents only -- price includes GST).  Sending a
   bank draft or money order is recommended.  Personal or corporate
   cheques drawn on a US bank (or on Canadian bank, in Canada) are
   acceptable.  Credit card orders are not accepted at this time.
   Please make cheques payable to Dendronic Decisions Limited.

   The software can be tried out using the Atree 3.0
   Educational Kit, available via anonymous ftp from ftp.cs.ualberta.ca
   in directory /pub/atree/atree3/. See files atree3ek.exe
   and atree3ek.brief.guide.
   The Educational Kit is restricted to learning functions with one or two
   inputs. A built-in 2D and 3D plotting capability is useful to help
   the user understand how ALNs work.

25. TDL v. 1.1 (Trans-Dimensional Learning)
+++++++++++++++++++++++++++++++++++++++++++

   Platform: Windows 3.*
   Company: Universal Problem Solvers, Inc.
   WWW-Site (UPSO): http://pages.prodigy.com/FL/lizard/index.html
   or FTP-Site (FREE Demo only): ftp.coast.net, in Directory:
   SimTel/win3/neurlnet, File: tdl11-1.zip and tdl11-2.zip
   Cost of complete program: US$20 + (US$3 Shipping and Handling).

   The purpose of TDL is to provide users of neural networks with a specific
   platform to conduct pattern recognition tasks.  The system allows for the fast
   creation of automatically constructed neural networks. There is no need to resort
   to manually creating neural networks and twiddling with learning parameters.
   TDL's Wizard can help you optimize pattern recognition accuracy. Besides
   allowing the application user to automatically construct neural network for a given
   pattern recognition task, the system supports trans-dimensional learning.  Simply put,
   this allows one to learn various tasks within a single network, which otherwise differ
   in the  number of input stimuli and output responses utilized for describing them.
   With TDL it is possible to incrementally learn various pattern recognition tasks within
   a single coherent neural network structure.  Furthermore, TDL supports the use of
   semi-weighted neural networks, which represent a hybrid cross between standard
   weighted neural networks and weightless multi-level threshold units. Combining both
   can result in extremely compact network structures (i.e., reduction in connections and
   hidden units), and improve predictive accuracy on yet unseen patterns. Of course the
   user has the option to create networks which only use standard weighted neurons.

   System Highlights:
   (1) The user is in control of TDL's memory system (can decide how many examples
   and neurons are allocated ; no more limitations, except for your computers memory).
   (2)TDLs Wizard supports hassle-free development of  neural networks, the goal of
   course being optimization of predictive accuracy on unseen patterns.
   (3) History option allows users to capture their favorite keystrokes and save them.
   Easy recall for future use.
   (4) Provides symbolic interface which allows the user to create:Input and output
   definition files, Pattern files, and Help files for objects (i.e., inputs, input values,
   and outputs).
   (5) Supports categorization of inputs.  This allows the user to readily access inputs
   via a popup menu within the main TDL menu.  The hierarchical structure of the
   popup menu is under the full control of the application developer (i. e., user).
   (6) Symbolic object manipulation tool: Allows the user to interactively design the
   input/output structure of an application.  The user can create, delete, or modify
   inputs, outputs,  input values, and categories.
   (7) Supports Rule representation: (a) Extends standard Boolean operators
   (i.e., and, or, not) to contain several quantifiers (i.e., atmost, atleast, exactly,
   between).  (b) Provides mechanisms for rule revision (i.e., refinement) and
   extraction. (c) Allows partial rule recognition. Supported are first- and best-fit.
   (8) Allows co-evolution of different subpopulations (based on type of transfer
   function chosen for each subpopulation).
   (9) Provides three types of crossover operators: simple random, weighted and blocked.
   (10) Supports both one-shot as well as multi-shot learning.  Multi-shot learning
   allows  for the incremental acquisition of different data sets.  A single expert
   network is constructed, capable of recognizing all the data sets supplied during
   learning. Quick context switching between different domains is possible.
   (11) Three types of local learning rules are included: perceptron, delta and fastprop.
   (12) Implements 7 types of unit transfer functions: simple threshold, sigmoid,
   sigmoid-squash, n-level threshold, new n-level-threshold, gaussian and linear.
   (13) Over a dozen statistics are collected during various batch training sessions.
   These can be viewed using the chart option.
   (14) A 140+ page hypertext on-line help menu is available.
   (15) A DEMONSTRATION of TDL can be invoked when initially starting the program.

26. NeurOn-Line
+++++++++++++++

   Built on Gensym Corp.'s G2(r), Gensym's NeurOn-Line(r) is a graphical,
   object-oriented software product that enables users to easily build
   neural networks and integrate them into G2 applications. NeurOn-Line is
   well suited for advanced control, data and sensor validation, pattern
   recognition, fault classification, and multivariable quality control
   applications. Gensym's NeurOn-Line provides neural net training and
   on-line deployment in a single, consistent environment. NeurOn-Line's
   visual programming environment provides pre-defined blocks of neural net
   paradigms that have been extended with specific features for real-time
   process control applications. These include: Backprop, Radial Basis
   Function, Rho, and Autoassociative networks. For more information on
   Gensym software, visit their home page at http://www.gensym.com. 

27. NeuFrame, NeuroFuzzy, NeuDesk and NeuRun
++++++++++++++++++++++++++++++++++++++++++++

      Name: NeuFrame, NeuroFuzzy, NeuDesk and NeuRun
   Company: NCS
   Address: Unit 3
            Lulworth Business Centre
            Totton
            Southampton
            UK
            SO40 3WW
     Phone: +44 (0)1703 667775
       Fax: +44 (0)1703 663730
     Email: robby@ncs-skylake.co.uk
       URL: http://www.demon.co.uk/skylake/software.html

   NeuFrame
   NeuFrame provides an easy-to-use, visual, object-oriented approach to
   problem solving using intelligence technologies, including nneural
   networks and neurofuzzy techniques. It provides features to enable
   businesses to investigate and apply intelligence technologies from
   initial experimentation through to building embedded implementations
   using software components.
   * Minimum Configuration- Windows 3.1 with win32s, 386DX 33MHz, 8Mb
     memory, 5Mb free disk space,VGA graphics, mouse
   * Recommended Configuration - Windows 95/NT 486DX 50MHz or above 16Mb
     memory,150Mb or above hard disc, VGA graphics, Mouse.
   * Price Commercial 749 (Pounds Sterling), Educational 435

   NeuroFuzzy
   This is an optional module for use within the NeuFrame enviroment. Fuzzy
   logic differs from neural networks in the sense that neural systems are
   constructed purely from available data whereas fuzzy systems are expert
   designed. The relative merits of the two approaches is very much
   application dependent as it relies on the availability of training data
   and expert knowledge. Conventional knowledge based systems can also be
   used to represent expert knowledge within computer systems, but fuzzy
   logic provides a richer representation. Benefits include:
   i)Combines the benefits of rule based fuzzy logic and learning from
   experience of neural networks.
   ii) Automatically generate optimised neurofuzzy models.
   iii) Encapsulate expert fuzzy knowledge within the model.
   iv) Fuzzy models may be modified or created according to the data
   presented to the network.
   v) Includes a pure Fuzzy logic editor .
   * Requires NeuFrame
   * Price Commercial 249 (Pounds Sterling), Educational 149

   NeuDesk
   NeuDesk 2 makes the implementation of a neural network solution very
   accessible.  Running within the Windows 3 environment, NeuDesk 2 is easy
   for non-specialists to use.  Data required for training the neural
   network can be entered manually, by cut and paste from any other Windows
   application, or imported from a number of different file formats.
   Training the network is achieved by a few straightforward
   point-and-click operations.
   * Recommended Configuration - Microsoft Windows 3.0 or higher with a
     minimum of 2Mb RAM and 20Mbyte hard disk and mouse. 4Mb RAM, 387
     co-processor and a 40Mb hard disk are recommended.
   * Price Commercial 349 (Pounds Sterling), Educational 149

   NeuRun
   NeuRun provides for the embedding of intelligence technologies developed
   in NeuFrame or NeuDesk to be embedded into other programs and
   environments. NeuRun simplifies and speeds up the process of embedding
   neural networks in your favourite Windows applications to provide
   on-line intelligence for decisions, predictions, suggestions or
   classifications. Implementations are easy to duplicate and deploy and
   can be readily updated if the problem conditions change over time.
   Typical of the application programs that can be enhanced using NeuRun 3
   are:  Excel, Microsoft's spreadsheet for creating powerful data
   manipulations and analysis applications and Visual Basic which can be
   used to generate user defined screens and functions for custom operator
   interfaces, data entry forms, control panels etc.
   * Price Commercial 50 (Pounds Sterling), Educational 50

28. OWL Neural Network Library (TM)
+++++++++++++++++++++++++++++++++++

      Name: OWL Neural Network Library (TM)
   Company: HyperLogic Corporation
   Address: PO Box 300010
            Escondido, CA 92030
            USA
     Phone: +1 619-746-2765 
       Fax: +1 619-746-4089
     Email: prodinfo@hyperlogic.com 
       URL: http://www.hyperlogic.com/hl

   The OWL Neural Network Library provides a set of popular networks in
   the form of a programming library for C or C++ software development.
   The library is designed to support engineering applications as well as
   academic research efforts.

   A common programming interface allows consistent access to the various
   paradigms. The programming environment consists of functions for
   creating, deleting, training, running, saving, and restoring networks,
   accessing node states and weights, randomizing weights, reporting the
   complete network state in a printable ASCII form, and formatting
   detailed error message strings.

   The library includes 20 neural network paradigms, and facilitates the
   construction of others by concatenation of simpler networks. Networks
   included are:

   * Adaptive Bidirectional Associative Memories (ABAM), including
     stochastic versions (RABAM). Five paradigms in all.
   * Discrete Bidirectional Associative Memory (BAM), with individual
     bias weights for increased pattern capacity.
   * Multi-layer Backpropagation with many user controls such as batching,
     momentum, error propagation for network concatenation, and optional
     computation of squared error. A compatible, non-learning integer
     fixed-point version is included. Two paradigms in all.
   * Nonadaptive Boltzmann Machine and Discrete Hopfield Circuit.
   * "Brain-State-in-a-Box" autoassociator.
   * Competitive Learning Networks: Classical, Differential, and 
     "Conscience" version. Three paradigms in all.
   * Fuzzy Associative Memory (FAM).
   * "Hamming Network", a binary nearest-neighbor classifier.
   * Generic Inner Product Layer with user-defined signal function.
   * "Outstar Layer" learns time-weighted averages. This network,
     concatenated with Competitive Learning, yields the
     "Counterpropagation" network.
   * "Learning Logic" gradient descent network, due to David Parker.
   * Temporal Access Memory, a unidirectional network useful for
     recalling binary pattern sequences.
   * Temporal Pattern Network, for learning time-sequenced binary patterns.

   Supported Environments:
     The object code version of OWL is provided on MS-DOS format diskettes
     with object libraries and makefiles for both Borland and Microsoft C.
     An included Windows DLL supports OWL development under Windows. The
     package also includes Owgraphics, a mouseless graphical user interface
     support library for DOS.

     Both graphical and "stdio" example programs are included.

     The Portable Source Code version of OWL compiles without change on
     many hosts, including VAX, UINX, and Transputer. The source code
     package includes the entire object-code package.

   Price:
     USA and Canada: (US) $295 object code, (US) $995 with source
     Outside USA and Canada: (US) $350 object code, (US) $1050 with source
     Shipping, taxes, duties, etc., are the responsibility of the customer.

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

Next part is part 7 (of 7). Previous part is part 5. 

-- 

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.
