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QwikNet v2.23
Copyright (C)1996-2002 Craig Jensen
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INTRODUCTION
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QwikNet is a powerful, yet easy to use artificial
neural network simulator. QwikNet implements several
different algorithms to train a standard feed-
forward neural network in an easy-to-use graphical
environment. The shareware version is limited to
a maximum of 1 hidden layer with 10 hidden neurons
and a maximum of 500 patterns per training data file.
The registered version can accommodate up to 5 hidden
layers with no limits (besides hardware) on the
number of hidden neurons or training patterns.

You may evaluate this software free for 30 days,
after which you must either purchase the registered
version or delete the software from your machine.

Please feel free to distribute the ZIP file
to friends, associates, or to a computer bulletin board
system (BBS).


REGISTRATION
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There are two ways to register. You can print and fill
out the registration form in the file 'register.txt',
(also found in the help file), and mail it with your
US cash/check payment directly to the author. Or you
can register via Kagi Software by running the file
'register.exe' and following the instructions. Kagi
accepts many different payment methods including credit
cards and non-US funds. The registration fee is US $49.
Upon receipt of payment you will receive the full
registered version and all future upgrades for one year.


INSTALLATION
------------
QwikNet.exe, runs on Windows 9x/NT/2000/XP. The
registered version removes all practical limits on
network/data file size. A complete installation requires
less than 5 MB of disk space.

To install QwikNet unzip the file qwiknet.zip and
run the file setup.exe.


EXAMPLE DATA FILES
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Several example data files are included for testing:

SINCOS.TRN -     Training data file with one input (x)
        and two outputs Sin(x) and cos(x).
SINCOS.TST - Testing data for SINCOS.
SINCOS.WTS -    Example of saved weights.
SINCOS.NET -     SINCOS project file.

SECURITY.* -    A more complex data set for Power System Security
        analysis. The data set contains 33 inputs
        (power system features) and 1 output     
        (security classification).

XOR.* - XOR training data set.
        Two inputs and 1 output.

SPIRALS.* - The popular "Two spirals" data consisting of
        data coiled three times around the origin and
        around one another in the x-y plane. This is
        a very difficult task for back-propagation
        networks and their relatives.

**** NOTE: Acceptable performance on the two spirals problem
may be impossible given the limitations of the
shareware version of QwikNet. A 3D contour map
of the solved spirals problem is included in the
    QwikNet help file, it uses two hidden layers.


QUESTIONS/COMMENTS
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Please send any questions, comments or bug reports to:

    Craig Jensen
    2488 239th PL NE
    Sammamish, WA 98074 USA
    email - cjensen@kagi.com or qwiknet@attbi.com