havBpNet++ - C++ classes for implementing Feedforward, Simple Recurrent and Random-Order Recurrent Neural Nets trained by Backpropagation.
NN Demos havBpETT - NN Demo
An Example Trainer / Tester application using havBpNet++ to implement Feedforward, Simple Recurrent and Random-Order Recurrent Neural Nets trained by Backpropagation.  Screen shots 
Below are the FREE downloadable, self-extracting demos that were built using the DLL version of havBpNet++. Freeware versions are the same as the fully functional demo simulator except that the network-save function is disabled.

Large versions contain all VB support files required. Small versions assume that you have certain VB support files that come with VB-Pro-3.0. Unless otherwise stated, all demos are run on Windows 3.1, 95 or NT.

Export Restrictions:

The havBpETT demo is distributed under the General License GTDR, per section 779.4 of the Export Administration Regulations of the United States Department of Commerce, Bureau of Export Administration. As such, neither it nor underlying information or technology may be downloaded or otherwise exported or re-exported (i) into (or to a national, resident or agent of) Cuba, Iraq, Libya, Sudan, North Korea, Iran, Syria or any other country to which the U.S. has embargoed goods; or (ii) to anyone on the U.S. Treasury Department's list of Specially Designated Nationals or the U.S. Department of Commerce's Table of Denial Orders. Furthermore, only hav.Software or it's designated agents may export any hav.Software product to the People's Republic of China.

By downloading or using the havBpETT++ demo, you are agreeing to the foregoing and you are representing and warranting that you are not located in, under the control of, or a national, resident or agent of any such country or on any such list.

Please feel free to play with and distribute these free demos as you wish (as long as you do not infringe the export restrictions noted above). Also, please let us know about any problems with any of the demos or with the download links below.

This new version adds support for recurrency and increases the number of nodes per layer from 200 to 1000. Several screen-shots are available for your review.

Large (@ 820 kb)
Small (@ 555 kb)

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