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From: saswss@unx.sas.com (Warren Sarle)
Subject: comp.ai.neural-nets FAQ, Part 1 of 7: Introduction
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Archive-name: ai-faq/neural-nets/part1
Last-modified: 1996-01-06
URL: ftp://ftp.sas.com/pub/neural/FAQ.html
Maintainer: saswss@unx.sas.com (Warren S. Sarle)


  ---------------------------------------------------------------
    Additions, corrections, or improvements are always welcome.
    Anybody who is willing to contribute any information,
    please email me; if it is relevant, I will incorporate it.

    The monthly posting departs at the 28th of every month.
  ---------------------------------------------------------------


This is the first of seven parts of a monthly posting to the Usenet
newsgroup comp.ai.neural-nets (as well as comp.answers and news.answers,
where it should be findable at any time). Its purpose is to provide basic
information for individuals who are new to the field of neural networks or
who are just beginning to read this group. It will help to avoid lengthy
discussion of questions that often arise for beginners. 

   SO, PLEASE, SEARCH THIS POSTING FIRST IF YOU HAVE A QUESTION
                           and
   DON'T POST ANSWERS TO FAQs: POINT THE ASKER TO THIS POSTING

The latest version of the FAQ is available as a hypertext document, readable
by any WWW (World Wide Web) browser such as Mosaic, under the URL: 
"ftp://ftp.sas.com/pub/neural/FAQ.html".

These postings are archived in the periodic posting archive on host
rtfm.mit.edu (and on some other hosts as well). Look in the anonymous ftp
directory "/pub/usenet/news.answers/ai-faq/neural-nets" under the file names
"part1", "part2", ... "part7". If you do not have anonymous ftp access, you
can access the archives by mail server as well. Send an E-mail message to
mail-server@rtfm.mit.edu with "help" and "index" in the body on separate
lines for more information.

For those of you who read this FAQ anywhere other than in Usenet: To read
comp.ai.neural-nets (or post articles to it) you need Usenet News access.
Try the commands, 'xrn', 'rn', 'nn', or 'trn' on your Unix machine, 'news'
on your VMS machine, or ask a local guru.

This FAQ is not meant to discuss any topic exhaustively.

Disclaimer: 

   This posting is provided 'as is'. No warranty whatsoever is expressed or
   implied, in particular, no warranty that the information contained herein
   is correct or useful in any way, although both are intended. 

To find the answer of question "x", search for the string "Subject: x"

And now, in the end, we begin: 

========== Questions ========== 
********************************

Part 1: Introduction

   What is this newsgroup for? How shall it be used?
   What is a neural network (NN)?
   What can you do with a Neural Network and what not?
   Who is concerned with Neural Networks?

Part 2: Learning

   What does 'backprop' mean? What is 'overfitting'?
   Why use a bias input? Why activation functions?
   How many hidden units should I use?
   How many learning methods for NNs exist? Which?
   What about Genetic Algorithms and Evolutionary Computation?
   What about Fuzzy Logic?
   How are NNs related to statistical methods?

Part 3: Information resources

   Good introductory literature about Neural Networks?
   Any journals and magazines about Neural Networks?
   The most important conferences concerned with Neural Networks?
   Neural Network Associations?
   Other sources of information about NNs?

Part 4: Datasets

   Databases for experimentation with NNs?

Part 5: Free software

   Freely available software packages for NN simulation?

Part 6: Commercial software

   Commercial software packages for NN simulation?

Part 7: Hardware

   Neural Network hardware?

------------------------------------------------------------------------

Subject: What is this newsgroup for? How shall it be
====================================================
used?
=====

The newsgroup comp.ai.neural-nets is intended as a forum for people who want
to use or explore the capabilities of Artificial Neural Networks or
Neural-Network-like structures.

There should be the following types of articles in this newsgroup:

1. Requests
+++++++++++

   Requests are articles of the form "I am looking for X", where X
   is something public like a book, an article, a piece of software. The
   most important about such a request is to be as specific as possible!

   If multiple different answers can be expected, the person making the
   request should prepare to make a summary of the answers he/she got and
   announce to do so with a phrase like "Please reply by email,
   I'll summarize to the group" at the end of the posting.

   The Subject line of the posting should then be something like 
   "Request: X" 

2. Questions
++++++++++++

   As opposed to requests, questions ask for a larger piece of information
   or a more or less detailed explanation of something. To avoid lots of
   redundant traffic it is important that the poster provides with the
   question all information s/he already has about the subject asked and
   state the actual question as precise and narrow as possible. The poster
   should prepare to make a summary of the answers s/he got and announce to
   do so with a phrase like "Please reply by email, I'll
   summarize to the group" at the end of the posting.

   The Subject line of the posting should be something like "Question:
   this-and-that" or have the form of a question (i.e., end with a
   question mark) 

3. Answers
++++++++++

   These are reactions to questions or requests. As a rule of thumb articles
   of type "answer" should be rare. Ideally, in most cases either the answer
   is too specific to be of general interest (and should thus be e-mailed to
   the poster) or a summary was announced with the question or request (and
   answers should thus be e-mailed to the poster).

   Most news-reader software automatically provides a subject line beginning
   with "Re:" followed by the subject of the article which is being
   followed-up. Note that sometimes longer threads of discussion evolve from
   an answer to a question or request. In this case posters should change
   the subject line suitably as soon as the topic goes too far away from the
   one announced in the original subject line. You can still carry along the
   old subject in parentheses in the form "Subject: new subject
   (was: old subject)" 

4. Summaries
++++++++++++

   In all cases of requests or questions the answers for which can be
   assumed to be of some general interest, the poster of the request or
   question shall summarize the answers he/she received. Such a summary
   should be announced in the original posting of the question or request
   with a phrase like "Please answer by email, I'll
   summarize"

   In such a case, people who answer to a question should NOT post their
   answer to the newsgroup but instead mail them to the poster of the
   question who collects and reviews them. After about 5 to 20 days after
   the original posting, its poster should make the summary of answers and
   post it to the newsgroup.

   Some care should be invested into a summary: 
    o simple concatenation of all the answers is not enough: instead,
      redundancies, irrelevancies, verbosities, and errors should be
      filtered out (as well as possible) 
    o the answers should be separated clearly 
    o the contributors of the individual answers should be identifiable
      (unless they requested to remain anonymous [yes, that happens]) 
    o the summary should start with the "quintessence" of the answers, as
      seen by the original poster 
    o A summary should, when posted, clearly be indicated to be one by
      giving it a Subject line starting with "SUMMARY:" 
   Note that a good summary is pure gold for the rest of the newsgroup
   community, so summary work will be most appreciated by all of us. Good
   summaries are more valuable than any moderator ! :-) 

5. Announcements
++++++++++++++++

   Some articles never need any public reaction. These are called
   announcements (for instance for a workshop, conference or the
   availability of some technical report or software system).

   Announcements should be clearly indicated to be such by giving them a
   subject line of the form "Announcement: this-and-that" 

6. Reports
++++++++++

   Sometimes people spontaneously want to report something to the newsgroup.
   This might be special experiences with some software, results of own
   experiments or conceptual work, or especially interesting information
   from somewhere else.

   Reports should be clearly indicated to be such by giving them a subject
   line of the form "Report: this-and-that" 

7. Discussions
++++++++++++++

   An especially valuable possibility of Usenet is of course that of
   discussing a certain topic with hundreds of potential participants. All
   traffic in the newsgroup that can not be subsumed under one of the above
   categories should belong to a discussion.

   If somebody explicitly wants to start a discussion, he/she can do so by
   giving the posting a subject line of the form " Discussion:
   this-and-that"

   It is quite difficult to keep a discussion from drifting into chaos, but,
   unfortunately, as many many other newsgroups show there seems to be no
   secure way to avoid this. On the other hand, comp.ai.neural-nets has not
   had many problems with this effect in the past, so let's just go and
   hope... 

------------------------------------------------------------------------

Subject: What is a neural network (NN)?
=======================================

First of all, when we are talking about a neural network, we *should*
usually better say "artificial neural network" (ANN), because that is what
we mean most of the time. Biological neural networks are much more
complicated in their elementary structures than the mathematical models we
use for ANNs.

A vague description is as follows:

An ANN is a network of many simple processors ("units"), each possibly
having a (small amount of) local memory. The units are connected by
unidirectional communication channels ("connections"), which carry numeric
(as opposed to symbolic) data. The units operate only on their local data
and on the inputs they receive via the connections.

The design motivation is what distinguishes neural networks from other
mathematical techniques:

A neural network is a processing device, either an algorithm, or actual
hardware, whose design was motivated by the design and functioning of human
brains and components thereof.

Most neural networks have some sort of "training" rule whereby the weights
of connections are adjusted on the basis of presented patterns. In other
words, neural networks "learn" from examples, just like children learn to
recognize dogs from examples of dogs, and exhibit some structural capability
for generalization.

Neural networks normally have great potential for parallelism, since the
computations of the components are independent of each other. 

------------------------------------------------------------------------

Subject: What can you do with a Neural Network and
==================================================
what not?
=========

In principle, NNs can compute any computable function, i.e. they can do
everything a normal digital computer can do. Especially anything that can be
represented as a mapping between vector spaces can be approximated to
arbitrary precision by feedforward NNs (which is the most often used type).

In practice, NNs are especially useful for mapping problems which are
tolerant of some errors, have lots of example data available, but to which
hard and fast rules cannot easily be applied. NNs are, at least today,
difficult to apply successfully to problems that concern manipulation of
symbols and memory. 

------------------------------------------------------------------------

Subject: Who is concerned with Neural Networks?
===============================================

Neural Networks are interesting for quite a lot of very dissimilar people: 

 o Computer scientists want to find out about the properties of non-symbolic
   information processing with neural nets and about learning systems in
   general. 
 o Statisticians use neural nets as flexible, nonlinear regression and
   classification models. 
 o Engineers of many kinds exploit the capabilities of neural networks in
   many areas, such as signal processing and automatic control. 
 o Cognitive scientists view neural networks as a possible apparatus to
   describe models of thinking and conscience (High-level brain function). 
 o Neuro-physiologists use neural networks to describe and explore
   medium-level brain function (e.g. memory, sensory system, motorics). 
 o Physicists use neural networks to model phenomena in statistical
   mechanics and for a lot of other tasks. 
 o Biologists use Neural Networks to interpret nucleotide sequences. 
 o Philosophers and some other people may also be interested in Neural
   Networks for various reasons. 

------------------------------------------------------------------------

Next part is part 2 (of 7). 

-- 

Warren S. Sarle       SAS Institute Inc.   The opinions expressed here
saswss@unx.sas.com    SAS Campus Drive     are mine and not necessarily
(919) 677-8000        Cary, NC 27513, USA  those of SAS Institute.
