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Section - Commercial software packages for NN

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Top Document: FAQ, Part 6 of 7: Commercial software
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Since the FAQ maintainer works for a software company, he does not recommend
or evaluate software in the FAQ. The descriptions below are provided by the
developers or distributors of the software. 

Note for future submissions: Please restrict product descriptions to a
maximum of 60 lines of 72 characters, in either plain-text format or,
preferably, HTML format. If you include the standard header (name, company,
address, etc.), you need not count the header in the 60 line maximum. Please
confine your HTML to features that are supported by primitive browsers,
especially NCSA Mosaic 2.0; avoid tables, for example--use <pre> instead.
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

The following simulators are described below: 

1. BrainMaker 
2. SAS Enterprise Miner Software 
3. NeuralWorks 
4. MATLAB Neural Network Toolbox 
5. Propagator 
6. NeuroForecaster 
7. Products of NESTOR, Inc. 
8. Ward Systems Group (NeuroShell, etc.) 
9. Neuralyst 
10. Cortex-Pro 
11. Partek 
12. NeuroSolutions 
13. Qnet For Windows Version 2.0 
14. NeuroLab, A Neural Network Library 
15. hav.Software: havBpNet++, havFmNet++, havBpNet:J 
16. IBM Neural Network Utility 
17. NeuroGenetic Optimizer (NGO) Version 2.0 
18. WAND 
19. The Dendronic Learning Engine 
20. TDL v. 1.1 (Trans-Dimensional Learning) 
21. NeurOn-Line 
22. Neuframe 
23. OWL Neural Network Library (TM) 
24. Neural Connection 
25. Pattern Recognition Workbench Expo/PRO/PRO+ 
26. PREVia 
27. Trajan 2.1 Neural Network Simulator 
28. DataEngine 
29. Machine Consciousness Toolbox 
30. Professional Basis of AI Backprop 
31. STATISTICA: Neural Networks 
32. Braincel (Excel add-in) 
34. Viscovery SOMine 
35. NeuNet Pro 
36. Neuronics 
37. RG Software 
38. Cobalt A.I. Code Builder - Neural Network Edition 
39. NEURO MODEL and GenOpt 

See also 

1. BrainMaker

         Product: BrainMaker, BrainMaker Pro
         Company: California Scientific Software
         Address: 10024 Newtown rd, Nevada City, CA, 95959 USA
           Phone: 800 284-8112, 530 478 9040
             Fax: 530 478 9041
      Basic capabilities:  train backprop neural nets
      Operating system:   Windows, Mac
      System requirements:
      Approx. price:  $195, $795

      BrainMaker Pro 3.7 (DOS/Windows)     $795
          Gennetic Training add-on         $250
      BrainMaker 3.7 (DOS/Windows/Mac)     $195
          Network Toolkit add-on           $150
      BrainMaker 3.7 Student version       (quantity sales only, about $38 each)

      BrainMaker Pro CNAPS Accelerator Board $8145

      Introduction To Neural Networks book $30

      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 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.
           Full menu and dialog box interface, runs Backprop at 3,000,000 cps
           on a 300Mhz Pentium II; 570,000,000 cps on CNAPS accelerator.

      ---Features ("P" means is available in professional version only):
      MMX instruction set support for increased computation speed,
      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

2. SAS Enterprise Miner Software

    Product: SAS Enterprise Miner Solution

             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 
      Phone: (919) 677-8000          (49) 6221 4160
        Fax: (919) 677-4444          (49) 6221 474 850


   To find the addresses and telephone numbers of other SAS Institute
   offices, including those outside the USA and Europe, connect your web
   browser to 

   Enterprise Miner is an integrated software product that provides an
   end-to-end business solution for data mining based on SEMMA methodology
   (Sample, Explore, Modify, Model, Assess). Statistical tools include
   clustering, decision trees, linear and logistic regression, and neural
   networks. Data preparation tools include outlier detection, variable
   transformations, random sampling, and the partitioning of data sets (into
   training, test, and validation data sets). Advanced visualization tools
   enable you to quickly and easily examine large amounts of data in
   multidimensional histograms, and to graphically compare modeling results.

   The neural network tool includes 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, categorical
   variables, standardization of inputs and targets, and multiple
   preliminary optimizations from random initial values to avoid local
   minima. Training is done by powerful numerical optimization algorithms
   instead of tedious backprop. 

3. NeuralWorks

    Product: NeuralWorks Professional II Plus
             NeuralWorks Predict
    Company: NeuralWare
     Adress: 230 East Main Street
             Suite 200
             Carnegie, PA 15106-2700
      Phone: (412) 278-6280
        FAX: (412) 278-6289


   NeuralWorks Professional II/PLUS is a comprehensive neural network
   development environment. Professional II/PLUS is available for UNIX,
   Linux, and Windows operating systems on a variety of hardware platforms;
   data and network files are fully interchangeable. The Professional
   II/PLUS package contains comprehensive documentation that addresses the
   entire neural network development and deployment process, including a
   tutorial, a guide to neural computing, standard and advanced reference
   manuals, and platform-specific installation and user guides. 

   NeuralWare's proprietary InstaNet facility allows quick generation of a
   neural network based on any one of 28 standard neural network
   architectures described in neural network literature. After a network is
   created, all parameters associated with it can be directly modified to
   more closely reflect the problem domain. Professional II/PLUS includes
   advanced features such as performance measure-based methods to inhibit
   over-fitting; automatic optimization of hidden layer size and the ability
   to prune hidden units; and an Explain facility that indicates which
   network inputs most influence network outputs. 

   NeuralWorks Predict is an integrated tool for rapidly creating and
   deploying prediction and classification applications. Predict combines
   neural network technology with genetic algorithms, statistics, and fuzzy
   logic to automatically find solutions for a wide range of problems.
   Predict incorporates years of modeling and analysis experience gained
   from working with customers faced with a wide variety of analysis and
   interpretation problems. 

   Predict requires no prior knowledge of neural networks. With only minimal
   user involvement it addresses the issues associated with building robust
   models from available empirical data. Predict analyzes input data to
   identify appropriate transforms, partitions the input data into training
   and test sets, selects relevant input variables, and then constructs,
   trains, and optimizes a neural network tailored to the problem. For
   advanced users, Predict also offers direct access to all key training and
   network parameters. 

4. MATLAB Neural Network Toolbox

   The Mathworks Inc.
   3 Apple Hill Drive
   Natck, MA 01760
   Phone: 508-647-7000 
     Fax: 508-647-7001

   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.

5. Propagator

     Contact: ARD Corporation,
              9151 Rumsey Road, Columbia, MD  21045, USA
     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
     Windows Demo on:        /pub/msdos/windows/demo     /pub/msdos/neural_nets
     pkzip 2.04g archive file
           gatordem.txt    readme text file

6. NeuroForecaster & VisuaData

      Product: 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

   Neuroforecaster 4.1a for Windows is priced at US$1199 per single user
   license. Please email for order form. 

   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) 
    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
    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
    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 
   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. 

7. Products of NESTOR, Inc.

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

   Dr. Leon Cooper (having a Nobel Prize) 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.

8. Ward Systems Group (NeuroShell, etc.)

   Product: NeuroShell Predictor, NeuroShell Classifier, 
            NeuroShell Run-Time Server, NeuroShell Trader,
            NeuroShell Trader Professional, NeuroShell 2,
            GeneHunter, NeuroShell Engine
   Company: Ward Systems Group, Inc.
   Address: Executive Park West
            5 Hillcrest Drive
            Frederick, MD 21702
     Phone: 301 662-7950
       FAX: 301 662-5666

   Ward Systems Group Product Descriptions: 

    o NeuroShell. Predictor - This product is used for forecasting and
      estimating numeric amounts such as sales, prices, workload, level,
      cost, scores, speed, capacity, etc. It contains two of our newest
      algorithms (neural and genetic) with no parameters for you to have to
      set. These are our most powerful networks. Reads and writes text

    o NeuroShell. Classifier - The NeuroShell Classifier solves
      classification and categorization problems based on patterns learned
      from historical data. The Classifier produces outputs that are the
      probabilities of the input pattern belonging to each of several
      categories. Examples of categories include {acidic, neutral,
      alkaline}, {buy, sell, hold}, and {cancer, benign}. Like the
      NeuroShell Predictor, it has the latest neural and genetic classifiers
      with no parameters to set. These are our most powerful networks. It
      also reads and writes text files. 

    o NeuroShell. Run-Time Server - The NeuroShell Run-Time Server allows
      you to distribute networks created with the NeuroShell Predictor or
      NeuroShell Classifier from either a simple interface, from your own
      computer programs, or from Excel spreadsheets. 

    o NeuroShell Trader. - This is the complete product for anyone trading
      stocks, bonds, futures, commodities, currencies, derivatives, etc. It
      works the way you think and work: for example, it reads open, high,
      low, close type price streams. It contains charting, indicators, the
      latest neural nets, trading simulations, data downloading, and walk
      forward testing, all seamlessly working together to make predictions
      for you. The NeuroShell Trader contains our most powerful network

    o NeuroShell Trader. Professional - The Professional incorporates the
      original Trader along with the ability to optimize systems with a
      genetic algorithm even if they don't include neural nets! For example,
      you can enter a traditional trading strategy (using crossovers and
      breakouts) and then find optimal parameters for those crossovers and
      breakouts. You can also use the optimizer to remove useless rules in
      your trading strategy. 

    o NeuroShell. 2 - This is our classic general purpose system highly
      suited to students and professors who are most comfortable with
      traditional neural nets (not recommended for problem solving in a
      business or scientific environment). It contains 16 traditional neural
      network paradigms (algorithms) and combines ease of use and lots of
      control over how the networks are trained. Parameter defaults make it
      easy for you to get started, but provide generous flexibility and
      control later for experimentation. Networks can either predict or
      classify. Uses spreadsheet files, but can import other types. Runtime
      facilities include a source code generator, and there are several
      options for processing many nets, 3D graphics (response surfaces), and
      financial or time series indicators. It does not contain our newest
      network types that are in the NeuroShell Predictor, the NeuroShell
      Classifier and the NeuroShell Trader. 

    o GeneHunter. - This is a genetic algorithm product designed for
      optimizations like finding the best schedules, financial indicators,
      mixes, model variables, locations, parameter settings, portfolios,
      etc. More powerful than traditional optimization techniques, it
      includes both an Excel spreadsheet add-in and a programmer's tool kit.

    o NeuroShell. Engine - This is an Active X control that contains the
      neural and genetic training methods that we have used ourselves in the
      NeuroShell Predictor, the NeuroShell Classifier, and the NeuroShell
      Trader. They are available to be integrated into your own computer
      programs for both training and firing neural networks. The NeuroShell
      Engine is only for the most serious neural network users, and only
      those who are programmers or have programmers on staff. 

   Contact us for a free demo diskette and Consumer's Guide to Neural

9. Neuralyst

   Product:  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. 

10. Cortex-Pro

   Cortex-Pro information is on WWW at:
   You can download a working demo from there.
   Contact: Michael Reiss (
   email: <>. 

11. Partek

   Partek is a young, growing company dedicated to providing our customers
   with the best software and services for data analysis and modeling. We do
   this by providing a combination of statistical analysis and modeling
   techniques and modern tools such as neural networks, fuzzy logic, genetic
   algorithms, and data visualization. These powerful analytical tools are
   delivered with high quality, state of the art software. 

   Please visit our home on the World Wide Web: 

   Partek Incorporated 
   5988 Mid Rivers Mall Dr. 
   St. Charles, MO 63304 
   voice: 314-926-2329 
   fax: 314-441-6881 

12. NeuroSolutions v3.0

            Product: NeuroSolutions
            Company: NeuroDimension, Inc.
            Address: 1800 N. Main St., Suite D4
                     Gainesville FL, 32609
              Phone: (800) 634-3327 or (352) 377-5144
                FAX: (352) 377-9009
   Operating System: Windows 95/98/Me/NT/2000
              Price: $195 - $1995 (educational discounts available)

   NeuroSolutions is a highly graphical neural network development tool for
   Windows 95/98/Me/NT/2000. This leading edge software combines a modular,
   icon-based network design interface with an implementation of advanced
   learning procedures, such as recurrent backpropagation, backpropagation
   through time and genetic optimization. The result is a virtually
   unconstrained environment for designing neural networks for research or
   to solve real-world problems. 

   Download a free evaluation copy from


    o Multilayer perceptrons (MLPs) 
    o Generalized Feedforward networks 
    o Modular networks 
    o Jordan-Elman networks 
    o Self-Organizing Feature Map (SOFM) networks 
    o Radial Basis Function (RBF) networks 
    o Time Delay Neural Networks (TDNN) 
    o Time-Lag Recurrent Networks (TLRN) 
    o Recurrent Networks (TLRN) 
    o General Regression Networks (GRNN) 
    o Probabilistic Networks (PNN) 
    o Neuro-Fuzzy Networks 
    o Support Vector Machines (SVM) 
    o User-defined network topologies 

   Learning Paradigms

    o Backpropagation 
    o Recurrent Backpropagation 
    o Backpropagation through Time 
    o Conjugate Gradient Learning 
    o Unsupervised Learning 
       o Hebbian 
       o Oja's 
       o Sanger's 
       o Competitive 
       o Kohonen 

   Advanced Features

    o ANSI C++ Source Code Generation 
    o Customized Components through DLLs 
    o Genetic Optimization 
    o Microsoft Excel Add-in -- NeuroSolutions for Excel 
       o Visual Data Selection 
       o Data Preprocessing and Analysis 
       o Batch Training and Parameter Optimization 
       o Sensitivity Analysis 
       o Automated Report Generation 
    o DLL Generation Utility -- The Custom Solution Wizard 
       o Encapsulate any supervised NeuroSolutions NN into a Dynamic Link
         Library (DLL) 
       o Use the DLL to embed a NN into your own Visual Basic, Microsoft
         Excel, Microsoft Access or Visual C++ application 
       o Support for both Recall and Learning networks available 
       o Simple protocol for sending the input data and retrieving the
         network response 
    o Comprehensive Macro Language 
    o Fully accessible from any OLE-compliant application, such as: 
       o Visual Basic 
       o Microsoft Excel 
       o Microsoft Access 

13. Qnet For Windows Version 2.0

   Vesta Services, Inc.
   1001 Green Bay Rd, Suite 196
   Winnetka, IL   60093
   Phone:   (708) 446-1655

   Trial Version Available: 

   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); (mail) 1001 Green Bay Rd, #196,
   Winnetka, IL 60093 

14. NeuroLab, A Neural Network Library

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

   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
   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
   A free demo can be downloaded by or Orders, questions or suggestions can be sent by
   e-mail to 

15. hav.Software: havBpNet++, havFmNet++, havBpNet:J

   Names:      havBpNet++
   Company:    hav.Software
               P.O. Box 354
               Richmond, Tx.  77406-0354 - USA
   Phone:      (281) 341-5035

    o 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

      NOTE: a freeware version (Save disabled) of the havBpETT demo may be
      downloaded from the hav.Software home-page: or by anonymous ftp from 

      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

    o 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

      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

    o havBpNet:J is a Java class library that implements feedforward, simple
      recurrent (sequential) and random-ordered recurrent nets trained by
      backpropagation. Used for both stand-alone and embedded network
      training and consultation applications and applets. 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, error threshold,
      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. 

      Platforms:  Java Virtual Machines - 1.0 and later

      Licensing:  No Royalties or other fees (except for OEM/Reseller)

      Price:      Individual License is $55.00
                  Site, Corporate and OEM/Reseller also available

      Media:      Electronic distribution only.

16. 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 

17. 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 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

   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

   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: 
    o 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
    o Walk Forward Train/Test/Validation model evaluation for assuring model
    o Easy input data lagging for Back Propagation neural models, 
    o Neural transfer functions and techniques that assure proper
      extrapolation of predicted variables to new highs, 
    o Confusion matrix viewing of Predicted vs. Desired results, 
    o Exportation of models to Excel 5.0 (Win 3.1) or Excel 7.0 (Win'95/NT)
      through an optional Excel Add-In 
    o 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)        

18. 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
   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: 
   To contact Novel Technical Solutions email: <>. 

19. The Dendronic Learning Engine

   The Dendronic Learning Engine (DLE) Software Development Kit (SDK) allows
   the user to easily program machine learning technology into high
   performance applications. Application programming interfaces to C and C++
   are provided. Supervised learning is supported, as well as the recently
   developed reinforcement learning of value functions and Q-functions. Fast
   evaluation on PC hardware is supported by ALN Decision Trees. 

   An ALN consists of linear functions with adaptable weights at the leaves
   of a tree of maximum and minimum operators. The tree grows automatically
   during training: a linear piece splits if its error is too high. The
   function computed by an ALN is piecewise linear and continuous, and can
   approximate any continuous function to any required accuracy. Statistics
   are reported on the fit of each linear piece to test data. 

   The DLE has been very successful in predicting electrical power loads in
   the Province of Alberta. The 24-hour ahead load for all of Alberta (using
   seven weather regions) was predicted using a single ALN. Visit to learn about other successful
   applications to ATM communication systems, walking prostheses for persons
   with incomplete spinal cord injury, and many other areas. 

   Operating Systems: Windows NT 4.0, 95 and higher. 

   Price: Prices for the SDK start at $3495 US for a single seat, and are
   negotiable for embedded learning systems. A runtime non-learning system
   can be distributed royalty-free. 

   The power of the DLE can be tried out using an interactive spreadsheet
   program, ALNBench. ALNBench is free for research, education and
   evaluation purposes. The program can be downloaded from (Please note the installation key given

   For further information please contact: 

   William W. Armstrong PhD, President
   Dendronic Decisions Limited
   3624 - 108 Street, NW
   Edmonton, Alberta,
   Canada T6J 1B4
   Tel. +1 403 421 0800
   (Note: The area code 403 changes to 780 after Jan. 25, 1999)

20. TDL v. 1.1 (Trans-Dimensional Learning)

   Platform: Windows 3.*
   Company: Universal Problem Solvers, Inc.
   WWW-Site (UPSO):
   or FTP-Site (FREE Demo only):, in Directory:
   SimTel/win3/neurlnet, File: and
   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
   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
   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

21. 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 

22. Neuframe

   Product: Neuframe v.4 - ActiveX Components
   Company: Neusciences
   Address: Unit 2
            Lulworth Business Centre
            SO40 3WW
     Phone: +44 023 80 664011

   Neuframe is an easy-to-use, visual, object-oriented approach to problem
   solving, allowing the user to embed intelligent technologies within their
   applications. Neuframe provides features that enable businesses to
   investigate and apply Intelligence Technologies from an initial low cost
   experimentation platform, through to the building of embedded
   implementations using software components. 

    o ODBC 
    o Data Pre-Processing 
    o Multi-Layered Perceptron 
    o Kohonen 
    o Kmeans 
    o Radial Basis Function 
    o Neuro-Fuzzy Logic 
    o Statistics and Graphics 
    o Code Extract and OLE for development use 

   Recommended Configuration - Windows 9X, NT4 or 2000, Pentium 200 with
   64Mb Ram

   Price: Commercial &pound;1295 - Educational &pound;777 (pounds sterling)

   ActiveX Components

   KMeans, Linear Regression, Data Encoder: Price &pound;150 each (pounds

   Multi-Layered Perceptron, Radial Basis Function, Projection Pursuit
   Regression, Kohonen: Price &pound;350 each (pounds sterling)

23. OWL Neural Network Library (TM)

   Product: OWL Neural Network Library (TM)
   Company: HyperLogic Corporation
   Address: PO Box 300010
            Escondido, CA 92030
     Phone: +1 619-746-2765 
       Fax: +1 619-746-4089

   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: 
    o Adaptive Bidirectional Associative Memories (ABAM), including
      stochastic versions (RABAM). Five paradigms in all. 
    o Discrete Bidirectional Associative Memory (BAM), with individual bias
      weights for increased pattern capacity. 
    o 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. 
    o Nonadaptive Boltzmann Machine and Discrete Hopfield Circuit. 
    o "Brain-State-in-a-Box" autoassociator. 
    o Competitive Learning Networks: Classical, Differential, and
      "Conscience" version. Three paradigms in all. 
    o Fuzzy Associative Memory (FAM). 
    o "Hamming Network", a binary nearest-neighbor classifier. 
    o Generic Inner Product Layer with user-defined signal function. 
    o "Outstar Layer" learns time-weighted averages. This network,
      concatenated with Competitive Learning, yields the
      "Counterpropagation" network. 
    o "Learning Logic" gradient descent network, due to David Parker. 
    o Temporal Access Memory, a unidirectional network useful for recalling
      binary pattern sequences. 
    o 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. 

   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. 

24. Neural Connection

    Product: Neural Connection
    Company: SPSS Inc.
    Address: 444 N. Michigan Ave., Chicago, IL 60611
      Phone: 1-800-543-2185
             1-312-329-3500 (U.S. and Canada)
        Fax: 1-312-329-3668 (U.S. and Canada)

   SPSS has offices worldwide.  For inquiries outside the U.S. and Canada, 
   please contact the U.S. office to locate the office nearest you.

   Operating system   : Microsoft Windows 3.1 (runs in Windows 95)
   System requirements: 386 pc or better, 4 MB memory (8MB recommended), 4 MB 
   free hard disk space, VGA or SVGA monitor, Mouse or other pointing device, 
   Math coprocessor strongly recommended
   Price: $995, academic discounts available

   Neural Connection is a graphical neural network tool which uses an
   icon-based workspace for building models for prediction, classification,
   time series forecasting and data segmentation.  It includes extensive
   data management capabilities so your data preparation is easily done
   right within Neural Connection.  Several output tools give you the
   ability to explore your models thoroughly so you understand your

   Modeling and Forecasting tools
   * 3 neural network tools: Multi-Layer Perceptron, Radial Basis Function, 
     Kohonen network
   * 3 statistical analysis tools: Multiple linear regression, Closest 
     class means classifier, Principal component analysis

   Data Management tools
   * Filter tool: transformations, trimming, descriptive statistics, 
     select/deselect variables for analysis, histograms
   * Time series window: single- or multi-step prediction, adjustable step 
   * Network combiner
   * Simulator
   * Split dataset: training, validation and test data
   * Handles missing values

   Output Options
   * Text output: writes ASCII and SPSS (.sav) files, actual values, 
     probabilities, classification results table, network output
   * Graphical output: 3-D contour plot, rotation capabilties, WhatIf? tool 
     includes interactive sensititivity plot, cross section, color contour
   * Time series plot

   Production Tools
   * Scripting language for batch jobs and interactive applications
   * Scripting language for building applications

   * User s guide includes tutorial, operations and algorithms
   * Guide to neural network applications

   Example Applications
   * Finance - predict account attrition
   * Marketing - customer segmentation
   * Medical - predict length of stay in hospital
   * Consulting - forecast construction needs of federal court systems
   * Utilities - predict number of service requests
   * Sales - forecast product demand and sales
   * Science - classify climate types

25. Pattern Recognition Workbench Expo/PRO/PRO+

   Name: Pattern Recognition Workbench Expo/PRO/PRO+ 
   Company: Unica Technologies, Inc. 
   Address: 55 Old Bedford Rd., Lincoln, MA 01773 USA 
   Phone, Fax: (617) 259-5900, (617) 259-5901 

   Basic capabilities: 
    o Supported architectures and training methods include backpropagation,
      radial basis functions, K nearest neighbors, Gaussian mixture, Nearest
      cluster, K means clustering, logistic regression, and more. 
    o Experiment managers interactively control model development by
      walking you through problem definition and set-up; 
       o Provides icon-based management of experiments and reports. 
       o Easily performs automated input feature selection searches and
         automated algorithm parameter searches (using intelligent search
         methods including genetic algorithms) 
       o Statistical model validation (cross-validation, bootstrap
         validation, sliding-window validation). 
    o "Giga-spreadsheets" hold 16,000 columns by 16 million rows of data
      each (254 billion cells)! 
    o Intelligent spreadsheet supports data preprocessing and manipulation
      with over 100 built-in macro functions. Custom user functions can be
      built to create a library of re-usable macro functions. 
    o C source code generation, DLLs, and real-time application linking via
      DDE/OLE links. 
    o Interactive graphing and data visualization (line, histogram, 2D and
      3D scatter graphs). 

   Operating system: Windows 3.1, WFW 3.11, Windows 95, Windows NT (16-
   and 32-bit versions available) 

   System requirements: Intel 486+, 8+ MB memory, 5+ MB disk space 

   Approx. price: software starts at $995.00 (call for more info) 
   Solving Pattern Recognition Problems text book: $49.95 
   Money-back guarantee 

   Comments: Pattern Recognition Workbench (PRW) is a comprehensive
   environment/tool for solving pattern recognition problems using neural
   network, machine learning, and traditional statistical technologies. With
   an intuitive, easy-to-use graphical interface, PRW has the flexibility to
   address many applications. With features such as automated model
   generation (via input feature selection and algorithm parameter
   searches), experiment management, and statistical validation, PRW
   provides all the necessary tools from formatting and preprocessing your
   data to setting up, running, and evaluating experiments, to deploying
   your solution. PRW's automated model generation capability can generate
   literally hundreds of models, selecting the best ones from a thorough
   search space, ultimately resulting in better solutions! 

26. PREVia

   PREVia is a simple Neural Network-based forecasting tool. The current
   commercial version is available in French and English (the downloadable
   version is in English). A working demo version of PREVia is available for
   download at: 

   Introducing Previa

   Based on a detailed analysis of the forecasting decision process, Previa
   was jointly designed and implemented by experts in economics and finance,
   and neural network systems specialists including both mathematicians and
   computer scientists. Previa thus enables the experimentation, testing,
   and validation of numerous models. In a few hours, the forecasting expert
   can conduct a systematic experimentation, generate a study report, and
   produce an operational forecasting model. The power of Previa stems from
   the model type used, i.e., neural networks. Previa offers a wide range of
   model types, hence allowing the user to create and test several
   forecasting systems, and to assess each of them with the same set of
   criteria. In this way, Previa offers a working environment where the user
   can rationalise his or her decision process. The hardware requirements of
   Previa are: an IBM-compatible PC with Windows 3.1 (c) or Windows95. For
   the best performance, an Intel 486DX processor is recommended. Previa is
   delivered as a shrink-wrapped application software, as well as a dynamic
   link library (DLL) for the development of custom software. The DLL
   contains all the necessary functions and data structures to manipulate
   time series, neural networks, and associated algorithms. The DLL can also
   be used to develop applications with Visual BasicTM. A partial list of

   * Definition of a forecast equation : *
     Definition of the variable to forecast and explanatory variables.
     Automatic harmonisation of the domains and periodicities involved in 
        the equation.
   * Choice of a neuronal model associated with the forecasting equation :  *
     Automatic or manual definition of multi-layered architectures.
     Temporal models with loop-backs of intermediate layers.
   * Fine-tuning of a neuronal model by training *
     Training by gradient back-propagation.
     Automatic simplification of architectures.
     Definition of training objectives by adaptation of the optimisation 
     Definition of model form constraints.
     Graphing of different error criteria.
   * Analysis of a neuronal model: *
     View of Hinton graph associated with each network layer.
     Connection weight editing.
     Calculation of sensitivity and elasticity of the variable to forecast, 
        in relation to the explanatory variables.
     Calculation of the hidden series produced by the neural network.
   * Neural Network-Based Forecasting *
     Operational use of a neural network.
   * Series Analysis *
     Visualisation of a series curve.  Editing of the series values.
     Smoothing (simple, double, Holt & Winters)
     Study of the predictability of a series (fractal dimension)
     Comparison of two series.  Visualisation of X-Y graphs.

27. Trajan 2.0 Neural Network Simulator

   Trajan Software Ltd,
   Trajan House,
   68 Lesbury Close,
   Co. Durham,
   DH2 3SR,
   United Kingdom.



   Tel: +44 191 388 5737. (8:00-22:00 GMT).


   Trajan 2.1 Professional is a Windows-based Neural Network includes
   support for a wide range of Neural Network types, training algorithms,
   and graphical and statistical feedback on Neural Network performance.

   Features include: 
   1. Full 32-bit power. Trajan 2.1 is available in a 32-bit version for
      use on Windows 95 and Windows NT platforms, supporting
      virtually-unlimited network sizes (available memory is a constraint).
      A 16-bit version (network size limited to 8,192 units per layer) is
      also available for use on Windows 3.1. 
   2. Network Architectures. Includes Support for Multilayer Perceptrons,
      Kohonen networks, Radial Basis Functions, Linear models, Probabilistic
      and Generalised Regression Neural Networks. Training algorithms
      include the very fast, modern Levenburg-Marquardt and Conjugate
      Gradient Descent algorithms, in addition to Back Propagation (with
      time-dependent learning rate and momentum, shuffling and additive
      noise), Quick Propagation and Delta-Bar-Delta for Multilayer
      Perceptrons; K-Means, K-Nearest Neighbour and Pseudo-Inverse
      techniques for Radial Basis Function networks, Principal Components
      Analysis and specialised algorithms for Automatic Network Design and
      Neuro-Genetic Input Selection. Error plotting, automatic cross
      verification and a variety of stopping conditions are also included. 
   3. Custom Architectures. Trajan allows you to select special
      Activation functions and Error functions; for example, to use Softmax
      and Cross-entropy for Probability Estimation, or City-Block Error
      function for reduced outlier-sensitivity. There are also facilities to
      "splice" networks together and to delete layers from networks,
      allowing you to rapidly create pre- and post-processing networks,
      including Autoassociative Dimensionality Reduction networks. 
   4. Simple User Interface. Trajan's carefully-designed interface gives
      you access to large amounts of information using Graphs, Bar Charts
      and Datasheets. Trajan automatically calculates overall statistics on
      the performance of networks in both classification and regression.
      Virtually all information can be transferred via the Clipboard to
      other Windows applications such as Spreadsheets. 
   5. Pre- and Post-processing. Trajan 2.1 supports a range of pre- and
      post-processing options, including Minimax scaling, Winner-takes-all,
      Unit-Sum and Unit-Length vector. Trajan also assigns classifications
      based on user-specified Accept and Reject thresholds.

   6. Embedded Use. The Trajan Dynamic Link Library gives full
      programmatic access to Trajan's facilities, including network
      creation, editing and training. Trajan 2.1 come complete with sample
      applications written in 'C' and Visual Basic.
   There is also a demonstration version of the Software available; please
   download this to check whether Trajan 2.1 fulfils your needs. 

28. DataEngine

   Product: DataEngine, DataEngine ADL, DataEngine V.i

   Company: MIT GmbH
   Address: Promenade 9
            52076 Aachen

     Phone: +49 2408 94580
       Fax: +49 2408 94582

   DataEngine is a software tool for data analysis implementing
   Fuzzy Rule Based Systems, Fuzzy Cluster Methods, Neural Networks,
   and Neural-Fuzzy Systems in combination with conventional methods
   of mathematics, statistics, and signal processing.

   DataEngine ADL enables you to integrate classifiers or controllers
   developed with DataEngine into your own software environment.  It
   is offered as a DLL for MS/Windows or as a C++ library for various
   platforms and compilers.

   DataEngine V.i is an add-on tool for LabView (TM) that enables you
   to integrate Fuzzy Logic and Neural Networks into LabView through
   virtual instruments to build systems for data analysis as well as
   for Fuzzy Control tasks.

29. Machine Consciousness Toolbox

   Can a machine help you understand the mechanisms of consciousness?
   A visual, interactive application for investigating artificial
   consciousness as inspired by the biological brain.
   Free, fully functional, introductory version with user manual and
   tutorials to download.
   Based on the MAGNUS neural architecture developed at Imperial College,
   London, UK.
   Developed by Novel Technical Solutions.
   Full information and download from: 

   [Note from FAQ maintainer: While this product explores some of the
   prerequisites of consciousness in an interesting way, it does not deal
   with deeper philosophical issues such as qualia.] 

30. Professional Basis of AI Backprop

   Backprop, rprop, quickprop, delta-bar-delta, supersab, recurrent networks
   for Windows 95 and Unix/Tcl/Tk. Includes C++ source, examples, hypertext
   documentation and the ability to use trained networks in C++ programs.
   $30 for regular people and $200 for businesses and government agencies.
   For details see: or 

   Questions to: Don Tveter, 

31. STATISTICA: Neural Networks

        Product: STATISTICA: Neural Networks version 4.0
        Company: StatSoft, Inc.
        Address: 2300 E. 14th St.
                 Tulsa, OK  74104
          Phone: (918) 749-1119
            Fax: (918) 749-2217

   STATISTICA Neural Networks is a comprehensive application capable of
   designing a wide range of neural network architectures, employing both
   widely-used and highly-specialized training algorithms. STATISTICA Neural
   Networks was developed by StatSoft, Inc., the makers of STATISTICA
   software, and is available and supported through a world-wide network of
   StatSoft subsidiaries. 

   The current version STATISTICA Neural Networks 4.0 offers features such
   as sophisticated training algorithms, an Intelligent Problem Solver that
   walks the user step-by-step through the analysis, a Neuro-Genetic Input
   Selection facility, a large selection of supplementary graphs and
   statistics (e.g., ROC, Response Surfaces, Sensitivity Analysis,
   Regression and Classification statistics), complete support for API
   (Application Programming Interface), and the ability to interface with
   STATISTICA data files and graphs. 

   STATISTICA Neural Networks includes traditional learning algorithms, such
   as back propagation and sophisticated training algorithms such as
   Conjugate Gradient Descent and Levenberg-Marquardt iterative procedures.
   Typically, choosing the right architecture of a neural network is a
   difficult and time-consuming "trial and error" process, but STATISTICA
   Neural Networks specifically does this for the user. STATISTICA Neural
   Networks features an Intelligent Problem Solver that utilizes heuristics
   and sophisticated optimization strategies to determine the best network
   architecture and walks the user step-by-step through the analysis. The
   Intelligent Problem Solver compares different network types (including
   Linear, Radial Basis Function, Multilayer Perceptron, and Bayesian
   networks), determines the number of hidden units, and chooses the
   Smoothing factor for Radial Basis Function networks. 

   The process of obtaining the right input variables in exploratory data
   analysis -- typically the case when neural networks are used -- also is
   facilitated by STATISTICA Neural Networks. Neuro-Genetic Input Selection
   procedures aid in determining the input variables that should be used in
   training the network. It uses an optimization strategy to compare the
   possible combinations of input variables to determine which set is most
   effective. STATISTICA Neural Networks offers complete API support so
   advanced users (or designers of corporate "knowledge seeking" or "data
   mining" systems) may be able to integrate the advanced computational
   engines of the Neural Networks module into their custom applications. 

   STATISTICA Neural Networks can be used as a stand-alone application or
   can interface directly with STATISTICA. It reads and writes STATISTICA
   data files and graphs. 

32. Braincel (Excel add-in)

        Product: Braincel
        Company: Promised Land Technologies 
        Address: 195 Church Street 11th Floor
                 New Haven, CT 06510
          Phone: (800) 243-1806 (Outside USA: (203) 562-7335)
            Fax: (203) 624-0655 
                 also see

   Braincel is an add-in to Excel using a training method called


        Product: DESIRE/NEUNET
        Company: G.A. and T.M. Korn Industrial Consultants 
        Address: 7750 South Lakeshore Road, # 15
                 Chelan, WA 98816 
          Phone: (509) 687-3390
          Price: $ 775 (PC)
                 $ 2700 (SPARCstation)
                 $ 1800 (SPARCstation/educational)
                 Free educational version

   DESIRE (Direct Executing SImulation in REal time) is a completely
   interactive system for dynamic-system simulation (up to 6,000
   differential equations plus up to 20,000 difference equations in scalar
   or matrix form; 13 integration rules) for control, aerospace, and
   chemical engineering, physiological modeling, and ecology. Easy
   programming of multirun studies (statistics, optimization). Complex
   frequency-response plots, fast Fourier transforms, screen editor,
   connection to database program. 

   DESIRE/NEUNET adds interactive neural-network simulation (to 20,000
   interconnections) and fuzzy logic. Simulates complete dynamic systems
   controlled by neural networks and/or fuzzy logic. Users can develop their
   own neural networks using an easily readable matrix notation, as in: 

    VECTOR layer2= tanh(W * layer1 + bias) 

   Over 200 examples include: 
    o backpropagation, creeping random search 
    o Hopfield networks, bidirectional associative memories 
    o perceptrons, transversal filters and predictors 
    o competitive learning, counterpropagation 
    o very fast emulation of adaptive resonance 
    o simulates fuzzy-logic control and radial-basis functions 


   Package includes 2 textbooks by G.A. Korn: "Neural Networks and
   Fuzzy-logic Control on Personal Computers and Workstations" (MIT Press,
   1995), and "Interactive Dynamic-system Simulatiuon under Windows 95 and
   NT" (Gordon and Breach, 1998). Please see our Web site for complete
   tables of contents of books, screen shots, list of users: 

   Complete educational versions of DESIRE/NEUNET for Windows 95 and NT can
   now be downloaded FREE as a .zip file which you un-zip to get an
   automatic INSTALLSHIELD installation program. The educational version is
   identical to our full industrial version except for smaller data areas (6
   instead of 6000 differential equations, smaller neural networks). It will
   run most examples from both textbooks. 

34. Viscovery SOMine

            Product: Viscovery SOMine
            Company: eudaptics software gmbh
            Address: Helferstorferstr. 5/8
                     A-1010 Vienna
              Phone: (+43 1) 532 05 70 
                Fax: (+43 1) 532 05 70 -21
   Operating System: Windows 95, Windows NT 4.0
             Prices: $1495 (commercial),  
                     $695 (non-commercial, i.e. universities)

   Viscovery SOMine is a powerful and easy-to-use tool for exploratory data
   analysis and data mining. Employing an enhanced version of Self
   Organizing Maps it puts complex data into order based on its similarity.
   The resulting map can be used to identify and evaluate the features
   hidden in the data. The result is presented in a graphical way which
   allows the user to analyze non-linear relationships without requiring
   profound statistical knowledge. The system further supports full pre- and
   postprocessing, cluster search, association/recall, prediction,
   statistics, filtering, and animated system state monitoring. Through the
   implementation of techniques such as SOM scaling, the speed in creating
   maps is increased compared to the original SOM algorithm. 

   Download a free evaluation copy from 

35. NeuNet Pro

      Product: NeuNet Pro
      Company: CorMac Technologies Inc.
      Address: 34 North Cumberland Street
               Thunder Bay, ON P7A 4L4
        Phone: (807) 345-7114
          Fax: (807) 345-7114

   NeuNet Pro is a complete neural network development system: 
    o Requires Windows 95, Windows 98, or Windows NT4(sp3). 
    o Powerful, easy to use, point and click, graphical development
    o Choose either SFAM or Back Propagation. 
    o Access data directly from MDB database file. 
    o Data may contain up to 255 fields. 
    o Split data into training set and testing set, up to 32,000 rows each. 
    o Comprehensive graphical reporting of prediction accuracy. 
    o Table browse, confusion matrix, scatter graph, and time series graph. 
    o Context sensitive help file with 70 page manual. 
    o Includes eight sample projects and assortment of sample data. 
    o Additional sample data available from URL above. 
    o Entire program may be downloaded from URL above. 

36. Neuronics

      Product: NNetView
      Company: Neuronics Inc.
      Address: Technoparkstr. 1
               CH-8005 Zurich Switzerland
        Phone: +41 1 445 16 40
          Fax: +41 1 445 16 44
   Operating systems: Windows 95/98/NT and on MacOS.
       Prices: 120 EUR for Simulator
               310 EUR for Full version incl. camera- and serial interface
               1260 EUR for Class licence

   NNetView is a simulator for neural networks that allows you to connect
   the network directly to the video camera input as well as the
   input/output of the serial port of your PC. In addition, the network can
   include a free architecture of 2-dimensional layers with connections in
   all directions. The most interesting feature is that you can combine
   different standard network types (such as Backpropagation, Hebb,
   Reinforcement Learning, Kohonen or Hopfield networks). NNetView allows to
   learn images (such as faces or colored objects) online and to make robots
   and other machines adaptive.

37. RG Software

    Product: NN50.DLL Neural Network Software Development Kit (SDK)
    Company: RG Software Corporation
    Address: 6838 W. Cholla
             Peoria, Arizona 85345
      Phone: (623) 773-2396
        FAX: (623) 334-3421

   The NN50.DLL Neural Network SDK allows you to incorporate a quickprop
   neural network in your favorite development environment (VB, FoxPro,
   C++, Assembler, Java and just about any other Windows programming
   language) with minimal investment and effort. NN50.DLL trains very fast,
   saves and loads weights, can be used online, stopped and called during
   training and more.  NN50's input relevance function is based on
   information gathered from
   NN50 is compatible with Windows 95, Windows 98, Windows NT and Windows
   2000. Unix and Linux versions are also available. Please see
   for details.  

38.  Cobalt A.I. Code Builder - Neural Network Edition
    Product: Code Builder - Neural Network Edition
    Company: Cobalt A.I. Software
      Phone: (623) 487-3813
      Price: U.S. $59.00

   Cobalt A.I. Code Builder - Neural Network
   Edition is a neural network source code
   generator. Design neural networks and generate
   efficient object oriented source code for C++,
   Java or Visual Basic (VB, Excel, Access, Word).
   Other languages (FoxPro, C# and VB.Net) will
   soon be integrated. Code Builder uses a "Project
   Wizard" to analyze data and suggest inputs, then
   generates source code accordingly. 

39. NEURO MODEL and GenOpt

    Product: NEURO MODEL and GenOpt 
    Company: ATLAN-tec KG
    Address: Hans-Martin Schleyer Strasse 18A
      Phone: +49 2154 92 48 222
        FAX: +49 2154 92 48 100

   Neuro Model (NM) is a Windows based ANN
   Development Package which does not require any
   scientific knowledge of ANN. Designed for the
   process industry, NM showed its best performance
   with real world data sets. Preprocessing of all
   data sets by a proprietary cluster algorithm
   provide reliable and consistant information for
   training. The internal combination of different
   mathematical methods eliminates the problem of
   local optima and overfitting. Modelling of
   dynamic non-linearity with implemented time
   behaviour enables the package to predict process
   conditions online in complexe enviroments like
   chemical reactors. Extensive reports of all net
   details include information about training
   parameters and statistics alerts. Software
   validation conform FDA could be done by
   worldwide co-operation with Pharmaplan
   Ask for FREE (Fullversion on loan) student
   License for your project. 

    o Customized Components through DLLs 
    o Non Linear Genetic Optimization through GEN
    o Microsoft Excel Add-in - NM Runtimer for Excel
    o Runtimer for Windows NT, 2000, UNIX, DEC-VAX,
    o Visual Data Selection 
    o Data Preprocessing, Analysis and Modification 
    o Batch Training and Parameter Optimization 
    o Extensive Information by different Sensitivity
      and Accuracy Analysis 
    o Security Net Algorithm shows statistical
      confidence for predicted results 
    o Comparison of predicted vs. desired results
      incl. confidence range for the whole
    o Automated Report Generation incl. DES crypted
    o Sophisticated Graphic Machine 
    o Multi Language Library for international
      Corporate Licenses 

   Applications References available for: 

    o Pharma & Bioscience 
    o Clinical Medicine Research 
    o Chemical Industry 
    o Waste Water Treatment Plants 
    o Food Industry 
    o Plastic Processing 
    o Prediction of Energy Consumption Behaviour for
      Electricity / Water / Gas network 


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

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