From: "Josiah Bryan" <jdb@wcoil.com>
Newsgroups: comp.lang.perl.announce,comp.lang.perl.modules
Subject: ANNOUNCE: AI::NeuralNet::Mesh 0.20
Date: 23 Aug 2000 05:48:14 GMT

Greets!
This is to announce the first public release of:

    AI::NeuralNet::Mesh, version 0.20

(AI::NeuralNet::Mesh is an optimized, accurate neural network Mesh.)

This module is available for download at: (***recomended download url***)
http://josiah.countystart.com/modules/get.pl?mesh:clpa

This file has also entered the CPAN as:
  file: $CPAN/authors/id/J/JB/JBRYAN/AI-NeuralNet-Mesh-0.20.zip
  size: 44366 bytes

** What is this?

AI::NeuralNet::Mesh is an optimized, accurate neural network Mesh.
It was designed with accruacy and speed in mind. This better learning
accuracy (by twenty-three percent), as well as a much faster learning
rate and run speed over any other neural network simulater that I know
of in Perl.(*)

Included are fifteen seperate example scripts. In particular
demonstration of the accuracy and speed of this network model, check
out ex_add2.pl, ex_dow.pl, and ex_add.pl

** Got more details?

Sure do:

>From the POD:
AI::NeuralNet::Mesh is an optimized, accurate neural network Mesh.
It was designed with accruacy and speed in mind. This is a neural
net simulator similar to AI::NeuralNet::BackProp, but with several
important differences. The two APIs are the same, that of this module
and ::BackProp, so any scripts that use ::BackProp, should be able
to use this module without (almost) any changes in your code. (The
only changes needed will be to change the "use" line and the "new"
constructor line to use ::Mesh instead of ::BackProp.)

This is a complete, from-scratch re-write of the Perl module
AI::NeuralNet::BackProp. It a method of learning similar to
back propogation, yet with a few custom modifications, includeding
a specialized output layer, as well as a better descent model for
learning.

Almost all of the notes and description in AI::NeuralNet::BackProp
apply to this module, yet the differences are detailed in the POD. I
also have included a complete working function refrence in the POD,
with any necessary updates added.


** What do you think?

Now I know you people are out there that are using the module...
I can hear the fists hitting the keyboards in frustration. :-) Relieve
some of that frustration by e-mailing me and letting me know what
you think of the module and any suggestions you got.

Use it, let me know what you all think. This is just a
groud-up write of a neural network, no code stolen or
anything else. Don't expect a classicist view of nerual
networking here. I simply wrote from operating theory,
not math theory. Any die-hard neural networking gurus out
there? Let me know how far off I am with
this code! :-)

Regards,

        ~ Josiah Bryan, <jdb@wcoil.com>



(*) In regards to the speed claim: I only know of two neural networks
in Perl, AI::NeuralNet::Mesh (this module) and AI::NeuralNet::BackProp,
both of which I wrote. If someone else has written a neural-net in Perl
I would love to see how or what techniques you have used. I am sorry if
I have missed anybody's Perl neural-net. If I have, it was not an
intentional error on my part.


--
Josiah Bryan
VP of Product Development
TDCJ, Inc.
"Anything is possible."

vp@tdcj.com
http://www.josiah.countystart.com/

Tel: 937.316.6256