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Commercial software packages for NN simulation
- nn/xnn
- Name: nn/xnn
- Company: Neureka ANS
- Address: Klaus Hansens vei 31B
5037 Solheimsviken
NORWAY
- Phone: +47-55544163 / +47-55201548
- Email: arnemo@eik.ii.uib.no
- Basic capabilities:
Neural network development tool. nn is a language for specification of
neural network simulators. Produces C-code and executables for the
specified models, therefore ideal for application development. xnn is
a graphical front-end to nn and the simulation code produced by nn.
Gives graphical representations in a number of formats of any
variables during simulation run-time. Comes with a number of
pre-implemented models, including: Backprop (several variants), Self
Organizing Maps, LVQ1, LVQ2, Radial Basis Function Networks,
Generalized Regression Neural Networks, Jordan nets, Elman nets,
Hopfield, etc.
- Operating system: nn: UNIX or MS-DOS, xnn: UNIX/X-windows
- System requirements: 10 Mb HD, 2 Mb RAM
- Approx. price: USD 2000,-
- 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
- SAS Software/ Neural Net add-on
- Name: SAS Software
- Company: SAS Institute, Inc.
- Address: SAS Campus Drive, Cary, NC 27513, USA
- Phone,Fax: (919) 677-8000
- Email: saswss@unx.sas.com (Neural net inquiries only)
- Basic capabilities:
Feedforward nets with numerous training methods
and loss functions, plus statistical analogs of
counterpropagation and various unsupervised
architectures
- Operating system: Lots
- System requirements: Lots
Uses XMS or EMS for large models(PCs only): Runs under Windows, OS/2
- Approx. price: Free neural net software, but you have to license
SAS/Base software and preferably the SAS/OR, SAS/ETS,
and/or SAS/STAT products.
- Comments: Oriented toward data analysis and statistical applications
- NeuralWorks
- Name: NeuralWorks Professional II Plus (from NeuralWare)
- Company: NeuralWare Inc.
- Adress: Pittsburgh, PA 15276-9910
- Phone: (412) 787-8222
- FAX: (412) 787-8220
- 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.
- MATLAB Neural Network Toolbox (for use with Matlab 4.x)
- 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 by Richard Andrew Miles Outerbridge,
RAMO@UVPHYS.PHYS.UVIC.CA:) Matlab is spreading like
hotcakes (and the educational discounts are very impressive). The
newest release of Matlab (4.0) ansrwers the question "if you could only
program in one language what would it be?". The neural network
toolkit is worth getting for the manual alone. Matlab is available with
lots of other toolkits (signal processing, optimization, etc.) but I don't
use them much - the main package is more than enough. The nice thing
about the Matlab approach is that you can easily interface the neural
network stuff with anything else you are doing.
- 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
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
- NeuroForecaster
- Name: NeuroForecaster(TM)/Genetica 3.1
- Contact: Accel Infotech (S) Pte Ltd; 648 Geylang Road;
Republic of Singapore 1438; Phone: +65-7446863; Fax: +65-7492467
accel@solomon.technet.sg
- For IBM PC 386/486 with mouse, or compatibles MS Windows* 3.1,
MS DOS 5.0 or above 4 MB RAM, 5 MB available harddisk space min;
3.5 inch floppy drive, VGA monitor or above, Math coprocessor recommended.
Neuroforecaster 3.1 for Windows is priced at US$1199 per single user
license. Please email us (accel@solomon.technet.sg) for order form.
More information about NeuroForecaster(TM)/Genetical may be found in
ftp://ftp.technet.sg/Technet/user/accel/nfga40.exe
NeuroForecaster is a user-friendly neural network program specifically
designed for building sophisticated and powerful forecasting and
decision-support systems (Time-Series Forecasting, Cross-Sectional
Classification, Indicator Analysis)
- Features:
* GENETICA Net Builder Option for automatic network optimization
* 12 Neuro-Fuzzy Network Models
* Multitasking & Background Training Mode
* Unlimited Network Capacity
* Rescaled Range Analysis & Hurst Exponent to Unveil Hidden Market
Cycles & Check for Predictability
* Correlation Analysis to Compute Correlation Factors to Analyze the
Significance of Indicators
* Weight Histogram to Monitor the Progress of Learning
* Accumulated Error Analysis to Analyze the Strength of Input Indicators
Its user-friendly interface allows the users to build applications quickly,
easily and interactively, analyze the data visually and see the results
immediately.
The following example applications are included in the package:
* Credit Rating - for generating the credit rating of bank loan
applications.
* Stock market 6 monthly returns forecast
* Stock selection based on company ratios
* US$ to Deutschmark exchange rate forecast
* US$ to Yen exchange rate forecast
* US$ to SGD exchange rate forecast
* Property price valuation
* XOR - a classical problem to show the results are better than others
* Chaos - Prediction of Mackey-Glass chaotic time series
* SineWave - For demonstrating the power of Rescaled Range Analysis and
significance of window size
Techniques Implemented:
* GENETICA Net Builder Option - network creation & optimization based on
Darwinian evolution theory
* Backprop Neural Networks - the most widely-used training algorithm
* Fastprop Neural Networks - speeds up training of large problems
* Radial Basis Function Networks - best for pattern classification problems
* Neuro-Fuzzy Network
* Rescaled Range Analysis - computes Hurst exponents to unveil hidden
cycles & check for predictability
* Correlation Analysis - to identify significant input indicators
- 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 - one of the most
powerfull PC-Tools 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 that is far superior to that of other neural networks.
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.
- 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.
- Contact: Ward Systems Group, Inc.; Executive Park West; 5 Hillcrest
Drive; Frederick, MD 21702; USA; Phone: 301 662-7950; FAX: 301
662-5666. Contact us for a free demo diskette and Consumer's Guide
to Neural Networks.
- 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.
- 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. Comments: A simple model that is easy to use.
Integrates nicely into Microsoft Excel. Allows user to create, train, and
run backprop ANN models entirely within an Excel spreadsheet.
Provides macro functions that can be called from Excel macro's,
allowing you to build a custom Window's interface using Excel's
macro language and Visual Basic tools. The new version 1.4 includes a
genetic algorithm to guide the training process. A good bargain to boot.
(Comments by Duane Highley, a user and NOT the program developer.
dhighley@ozarks.sgcl.lib.mo.us)
- 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).
- 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:
.
- 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:
- 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 the most 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
- 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
- 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.
From: the comp.ai.neural-nets newsgroup.
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