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Forthcoming Releases:

Fuzzy Logic:
sFLC3
DLL & API

Neural Net:
Release of NXL3
DLL & API

Fall 2003

Essential links and references

Feel free to report links you think could be of interest to all neural net 'aficionados' to : support@foretrade.com		(Radio Classique widget on your desktop)
Comprehensive search for documents:
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Fellow traders, please bear with me. The following links and information below are more targeted to developers and other apprentice researchers. Please click here if you wish to skip this section.

This page is no longer regularly updated. Search engines do a great job nowadays...

A.I.

We always first recommend spending some time on these newsgroups:

comp.ai.neural-nets

comp.ai.fuzzy

comp.ai.genetic

comp.theory.cell-automata

sci.nonlinear

The above neural nets newsgroup has the most comprehensive FAQ available edited monthly by Warren Sarle on ftp://ftp.sas.com/pub/neural/ It is a little technical, but highly rewarding whether you intend building your own neural nets, or just better understanding how neural nets can work best for you. At the end of the day, better nets can only mean better systems, and more profitability.

More on Neural Nets:

A very good compilation of neural net info is available at: http://ai-depot.com/ or http://www.ai-junkie.com/ai-junkie.html.
There are a lot of interesting links and tutorials on neural nets and AI in general. Besides the obvious, i can suggest a general introduction on AI like the "MS Guidance" web page.
Now, If you want to go straight for an advanced neural toolbox, then my pick would be: http://grey.colorado.edu/emergent/index.php/Main_Page (regular updates) or
SNNS (older, and no recent update though).
Programmers may be also interested in taking a look at the Programmers Heaven's site as well as SourceForge.net.

Beginners should maybe first look at existing neural net shareware like EasyNN, or our own neural nets like NXL2, and VB BackProp on our neural net page. Too many traders have given up on neural nets just because they could not get their nets going right. Again, one must remain realistic, and can't expect much from "everything but the kitchen sink" types of neural nets.

Another good reference from the FAQ is Donald Tveter's site: http://www.dontveter.com/nnsoft/nnsoft.html. One must however not forget Genetic Algorithms, and the now well known FAQ "Hitch-Hiker's Guide to Evolutionary Computation"