HDTenEightyP/NetNews huggingface dataset:
From: james@library.nrl.navy.mil (James King)
Newsgroups: comp.multimedia,comp.sys.ibm.pc.hardware,sci.electronics
Subject: Re: Help finding a VGA --> TV Interface (PAL format)
Date: 13 Oct 92 12:24:08 GMT
Distribution: comp
Organization: NRL

In article <JON_SREE.92Oct10105946@world.std.com> jon_sree@world.std.com (Jon Sreekanth) writes:
>From: jon_sree@world.std.com (Jon Sreekanth)
>Subject: Help finding a VGA --> TV Interface (PAL format)
>Date: 10 Oct 92 15:59:46 GMT
>
>
>Sorry if this is a FAQ. We need a VGA to PAL format video converter.
>(Alternately, if you know of VGA to NTSC convertors, I'd appreciate 
>hearing about that, so I can ask the companies if they make a PAL version.)
>
>Any pointers would be greatly appreciated. I'm looking for company names 
>and phone numbers, so I can start making calls. 
>
>Please send email and I'll summarize. 
>
>Thanks,
>
>/ Jon Sreekanth
>
>Assabet Valley Microsystems, Inc.           |  Fax and PC products
>5 Walden St #3, Cambridge, MA 02140         |  (617) 876-8019
>jon_sree@world.std.com                      |

VideoLogic makes a box called a Mediator which can convert Macintosh's RGB 
or PC's VGA video signal to NTSC or PAL.  They also make plug-in boards 
for both the PC and the Macintosh that do the same thing.  The company info 
is:

VideoLogic, Inc.
245 First Street
Cambridge, MA  02142
617-494-0534
FAX: 617-494-0534

Hope it helps.


R. James King
Naval Research Lab
Washington, DC
Newsgroups: comp.multimedia
From: cs902125@ariel.yorku.ca (SHUK C YIP)
Subject: Re: Video Blaster Compared to Video Toaster?
Organization: York University, Toronto, Canada
Distribution: usa
Date: Fri, 9 Oct 1992 04:09:01 GMT

In article <1992Oct6.105604@hgc.edu> karen@hgc.edu (karen otto) writes:
>
>I've heard a lot about the Video Toaster.  Has anyone heard any-
>thing, good or bad, about the Video Blaster?  It's a product
>of the Creative Labs, Inc.
>

I think Video Blaster should compare with Impact Vision, not Video
Toaster because they are totally different.
Newsgroups: comp.multimedia
From: SBITCSC@KUBVX1.KUB.NL (P383 592188 Bosters)
Subject: Re: Soundmaster II drivers for WINDOWS 3.1 please :-)
Date: Fri, 16 Oct 92 14:17:49 GMT
Organization: Tilburg University, The Netherlands
X-News-Reader: VMS NEWS 1.22

In <17270013@hpgrla.gr.hp.com> galenr@hpgrla.gr.hp.com writes:

> In comp.multimedia, thorjc@dhhalden.no (THOR JOHAN CHRISTENSEN) writes:
> 
> >I have a SoundMaster II card from covox. And I need drivers for windows 3.1. 
> >Is there anyone who can tell me where I can find them ??
> >Thanks. 
> >Johan III- Norway
> 
> Just the following in the comp.os.ms-windows.programmer.misc  I dunno if there
> are any others (via FTP)??
> Good Luck!!
> - Galen -
> 
> >From: root@sean.tomsk.su (Alex Povzner)
> >Date: Thu, 8 Oct 1992 21:59:50 GMT
> >Subject: I've created COVOX(lpt' DAC) driver for Windows
> >
> >        Are You in need of COVOX (DAC) driver for Windows ? Such
> >driver allows to play .WAV and .MOD files under MS-Windows !
> >With simple DAC (Covox) scheme either on resistors or on DAC chip !
> >Any melody can be assigned to any Windows' internal event !
> >Almost any prrogram for Windows' Sound will work with Covox
> >Driver !
> >
> >        If You don't have COVOX driver and You want to receive it,
> >You send usual paper letter containing $5 and Your EMAil address
> >to me and in a one day after delivering of the letter You will
> >have had the driver.
> >
> >        My address : Russia, index 634034, town Tomsk,
> >        street Uchebnaya 34, 51. Alex Povzner

Be warned: this is NOT, repeat NOT, an driver for the SoundMaster II card
from COVOX. The Drivers can be obtained from Covox ltd. or if this would 
show to be difficult I'll send my drivers to you through the mail.

Succes and Greetings,


Jeroen Bosters

Tilburg University
The Netherlands
SBITCSC@KUB.NL
From: pheras@iris-dcp.es
Newsgroups: comp.ai
Subject: REGISTER
Date: 9 Oct 92 18:03:54 +0100
Organization: REDIRIS, Red Nacional de I+D

Needed info about automatic knowledge acquirement from written text.


	Some newsgroup about this topic?\

	Some articles, books, mail-lists.


	Please, send info to my e-mail address, or post here, in news.
From: wlb@progress.COM (Warren Bare)
Subject: Re: Papers Using neural Nets in Economics
Organization: Progress Software Corp.
Date: Fri, 9 Oct 1992 13:56:57 GMT


Are there ftp sites that carry these reports (or some of them)?

Warren

--
Warren L. Bare                UUCP: mit-eddie!progress!Warren.Bare
Progress Software Corp.   Internet: Warren.Bare@progress.com
14 Oak Park                    FAX: 1 617 275 4595
Bedford, MA  01730
From: honavar@iastate.edu (Vasant G Honavar)
Newsgroups: comp.ai.neural-nets
Subject: Re: Rosenblatt's book revisited
Date: 12 Oct 92 21:35:19 GMT
Article-I.D.: news.Bw12Mz.MIp
Organization: Brainstorms International

In article <Oct.12.13.02.47.1992.9523@control.rutgers.edu> sontag@control.rutgers.edu (Eduardo Sontag) writes:
>
>Puzzled by statements often made about Rosenblatt's original work, including
>those often seen in papers or grant proposals, which roughly state something
>like "he didn't realize that some functions such as XOR can't be computed...
>[until Minsky and Papert came along]...", I decided to take a quick look at
>the source, the book "Principles of Neurodynamics" (1962).  The purpose of
>this note is to try to clear some apparently popular missconceptions.

I am glad to see that I am not the only one who feels this way. I read 
parts of Rosenblatt's book a couple of years ago and was impressed by the
breadth of issues that he had addressed in it.  It is an interesting  
question as to where Rosenblatt or his contemporaries could have carried
this line of work if the state of the computer technology at the time was
anything like it is today.  There is probably a lot of interesting material
for people interested in the history and sociology of science here!   

Vasant Honavar
Computer Science & Neuroscience
Iowa State University
honavar@iastate.edu
From: prechelt@i41s18.ira.uka.de (Lutz Prechelt)
Newsgroups: comp.ai.neural-nets
Subject: Re: Question: how to represent a function
Date: 15 Oct 92 18:23:41 GMT
Organization: University of Karlsruhe, FRG
NNTP-Posting-Host: i41s18.ira.uka.de

In article <nijmanm.719141167@hpas7>, nijmanm@prl.philips.nl (M.J. Nijman) writes:
|> 
|> I am looking for a NN architecture plus learning rule to solve the
|> following problem:
|> 
|> There exists a fuction f(c,x) of which for some values of c the behaviour
|> as fuction of x is known, ...
...
|> What I'm looking for is a interpolation which would yield:
...interpolated reactions for unknown values of c.


If you have data for enough values of c, this is a nice one-dimensional 
function approximation problem and backprop should be suited wonderfully 
for it.

Just make both, x and c, inputs of the net (perhaps suitably 
scaled and distorted) and let f(x, c) be the only output,
also scaled and perhaps distorted.
With the right number of hidden units, this should work.

  Lutz


-- 
Lutz Prechelt   (email: prechelt@ira.uka.de)            | Whenever you 
Institut fuer Programmstrukturen und Datenorganisation  | complicate things,
Universitaet Karlsruhe;  D-7500 Karlsruhe 1;  Germany   | they get
(Voice: ++49/721/608-4317, FAX: ++49/721/694092)        | less simple.
Newsgroups: comp.ai.neural-nets
From: bryant@neural.Kodak.COM (Steve Bryant)
Subject: Re: SUMMARY: CRSP Stock Database
Organization: Eastman Kodak Co., Rochester, NY
Date: Thu, 8 Oct 92 17:28:34 GMT

In article <Bvt58A.CMA.1@cs.cmu.edu>, sef@sef-pmax.slisp.cs.cmu.edu writes:

>I wonder if it is a commercial use to train a neural net on this data
>(producing a set of weights that are related to, but that do not CONTAIN
>the info of the database), and then send that neural net out into the world
>to make some investments.  One (or one's high-priced lawyer) could argue
>that this is the same as educational use, except in this case you're
>educating a network and not a human student.  In either case, the database
>owner would not have a legitimate claim on the "student's" subsequent
>earnings in life.  I'm sure the database owners would see it differently,
>however.
>

This would fall under the catigory of "derivative work" and would be
protected. Use this test - Was your work essentially dependent on the use
of their intellectual property. If the answer is yes, you have probably
violated the protection rights to their property.

>This could be an interesting court case.  It probably won't happen because
>most people won't want to take unfair advantage of CRSP, and if anyone
>does, it would be awfully hard to detect and prove. 

 Yes, it would be very difficult to prove.
Newsgroups: comp.ai.neural-nets
From: batra@tigger.cs.Colorado.EDU (sajeev batra)
Subject: questions on PAC learning
Organization: University of Colorado, Boulder
Date: Sun, 11 Oct 1992 06:04:45 GMT


first, i would like to apologize if these questions have been asked 
before.

i am trying to learn about this  PAC (probably approximately correct)
learning concept.  What does it mean for something to be pac-learnable?

also, the term Vapnik-Chervonenkis (VC) dimension is thrown about 
quite often.  Where does this fit in?

and one more thing...  I have been trying to read Valiant's "Theory
of the Learnable" (Comm. of ACM, 1984, 1134-1142) paper.  I do not
understand it.  Could someone who has read it briefly summarize it at 
a level that i could comprehend (introductory level).  I have a small
background in neural nets and statistics.

posting or emailing comments would be good.  And please
try to make all points in an introductory level.

thank you.
sajeev.
Newsgroups: comp.ai.neural-nets
From: jmorris@hot.caltech.edu (John Morris)
Newsgroups: comp.ai.neural-nets,comp.ai,sci.engr.control
Subject: Re: Fuzzy logic references wanted
Date: 8 Oct 92 10:09:44
Organization: Caltech Control Lab
	<1992Sep30.155618.5972@til.til.com>
	<1992Oct6.233515.11897@Firewall.Nielsen.Com>
	<1992Oct7.163107.21447@til.til.com>
NNTP-Posting-Host: mean.mu.caltech.edu
In-reply-to: erik@maui.til.com's message of Wed, 7 Oct 1992 16:31:07 GMT

Sorry to butt in on this discussion but I have a few thoughts I'd like
to mention. First let me tell you my background is in control theory.
A fundamentally important issue control people must deal with is the
issue of multi-input, multi-output systems (MIMO). A key result of such
considerations is that control strategies which work well for single-
input systems (SISO) often DO NOT work at all with MIMO systems. For
example, suppose you have a 2 input, 2 output system and design a SISO
controller for each loop that has large gain and phase margins. Analysis
of the stability of the MIMO system with this controller can be
unstable to very small modelling uncertainty (arbitrarily small in fact).
(Sorry if this is becoming pedantic)

So the question I have is this:

Has anyone begun to consider MIMO implications of fuzzy systems? I have
spoken with quite a few fuzzy theorists and the current trend is to
either use tons of cross-mappings (which makes the system very
computationally unattractive) or treat the problem as a bunch of SISO
problems (which I hope you see is not a good thing to do). Both of
which are also quite ad hoc.

Thanks in advance for any correspondence. Also, direct responses which
aren't suitable for net posting should be mailed directly to me at the
adrress below.

John C. Morris             -----|-----     e-mail: jmorris@hot.caltech.edu
Caltech, M/C 116-81     *>=====[_][ )      work:   (818) 356-4855
Pasadena, CA  91125           _'_`_        FAX:    (818) 795-1547
Xref: sparky comp.ai.neural-nets:3939 comp.speech:124
From: dennis@asi.com (Dennis Walker)
Newsgroups: comp.ai.neural-nets,comp.speech
Subject: SPARC software for phoneme->speech
Date: 15 Oct 92 18:43:15 GMT
Article-I.D.: asi.1992Oct15.184315.13711
Distribution: usa
Organization: Adaptive Solutions, Inc.,  Beaverton Oregon

I am looking for a software package that takes ARPAbet
phonemes as input and produces speech output on the
speaker of a Sun SPARCstation.  This is to be used for
a real-time demonstration of T. Sejnowski's NetTalk
on our CNAPS SIMD computer.  Anybody know of such
a package?  Thanks in advance!

Dennis Walker
Customer Applications Engineer
Adaptive Solutions
Newsgroups: comp.ai.neural-nets
From: edstrom@hsc.ucalgary.ca (John Edstrom)
Newsgroups: comp.ai.neural-nets
Subject: Re: Do neurons fatigue?
Date: 13 Oct 92 15:51:52 GMT
Distribution: comp
Organization: Neuroscience Division, U of Calgary School of Medicine, Calgary, Alberta, Canada

In article <HUCKA.92Oct12015455@potomac.engin.umich.edu> hucka@engin.umich.edu writes:
>Hello,
>
>I would like to try to find out whether there is evidence for fatigue in
>neurons.  Specifically, I'm interested in finding out whether there is
>evidence for fatigue effects in non-receptor neurons in vertebrates, in
>particular in cortical cells.  By fatigue I mean a decrease in responsiveness
>of a particular cell as a result of continued stimulation, and not a process
>of habituation.
>

By receptor I assume you mean sensory.  If so the answer is yes.
This is a result of time- and voltage-dependent conductances which
often tend to limit the intensity of a response to a prolonged
influence and is found in many neurons.  These conductances are
sometimes modulatable so adaptation (what I'm interpreting "fatigue"
to mean) can be turned on, off, up or down in some circumstances.



>If any of you know about research that deals with this topic, please let me
>know via email.
>--
>-- Mike

It appears in many  places but is rarely called fatigue.  Look for
accomodation or adaptation instead.

>_____________________________________________________________________________
>Mike Hucka                     | Internet: hucka@engin.umich.edu    
>University of Michigan AI Lab  | 1101 Beal Ave., Ann Arbor, MI 48109-2110

John Edstrom | edstrom @ elmer.hsc.ucalgary.ca

--
 RM 2104, HSc Building,  Div. Neuroscience
 U. Calgary School of Medicine,  3330 Hospital Drive NW
 Calgary, Alberta       T2N 3Y4
 (403) 220 4493  (wk)
From: dld@magi.ncsl.nist.gov (Darrin Dimmick X4147)
Newsgroups: comp.ai.neural-nets
Subject: Set of isolated hand-print digit images via anonymous ftp
Date: 9 Oct 92 16:05:18 GMT
Organization: National Institute of Standards and Technology, Gaithersburg, MD

National Institute of Standards and Technology

Announces the availability of a set of isolated hand-print digit images via
anonymous ftp

+--------+
|   Fl3  |
+--------+

The distribution of isolated characters named "fl3" contains 3,471 total
characters from  49 different writers and is a subset of "NIST Special Database
1".   These characters have been spatially normalized to be 32 X 32 pixels and
have not been compressed. Each character file's ASCII header contains 
information including the class type found in the "ID" field delimited by 
double quotes, the resulting resolution of the image after spatial 
normalization, and which form and box the character was extracted from within
"NIST Special Database 1."

This distribution requires approximately 4.5 Megabytes of mass storage.

Included with the image data is source code and documentation for manipulating
IHEAD raster images distributed by NIST.  The source code was designed and 
tested to run on Sun hardware and is written in the 'C' programming language. 
Also contained in this distribution is an updated / corrected log for the 
historical data related to "NIST Special Database 1", "./doc/hsf.log".

This distribution, fl3, is being provided in the UNIX tar format and has been 
UNIX compressed on a Sun workstation. The information can be extracted
as follows:

	# ftp sequoyah.ncsl.nist.gov
	Name anonymous
	Passwd username@machine
	ftp> cd pub
	ftp> cd data
	ftp> binary
	ftp> mget fl3.tar.Z fl3.doc
        ftp> bye
        # cp fl3.tar.Z <install_dir>
	# cd <install_dir>
        # uncompress fl3.tar.Z
	# tar -xvf fl3.tar


Darrin L. Dimmick
dld@magi.ncsl.nist.gov
301-975-4147
-- 
Darrin L. Dimmick
National Institute of Standards and Technology
Bldg. 225/A216
Gaithersburg, MD. 20899
Xref: sparky comp.ai.neural-nets:3842 comp.ai:3838 bionet.neuroscience:444 comp.dsp:2319
From: nijmanm@prl.philips.nl (M.J. Nijman)
Subject: Question: how to represent a function
Organization: Philips Research Laboratories Eindhoven, Netherlands
Date: Thu, 15 Oct 1992 09:26:07 GMT


I am looking for a NN architecture plus learning rule to solve the
following problem:

There exists a fuction f(c,x) of which for some values of c the behaviour
as fuction of x is known, for example:

            _  ___
           / \/   \
f(0,x)    /        \
         /          \
        /            \

            ___  _
           /   \/ \
f(1,x)    /        \
         /          \
        /            \

What I'm looking for is a interpolation which would yield:

            __  __
           /  \/  \
f(0.5,x)  /        \
         /          \
        /            \

This cannot be solved using a 3-layer feedforward network where the
input is the first parameter of f and the output consists of a number
of neurons which represent the fuction by their activation, as follows:

            __  __
           /  \/  \
          /        \      activation of the output neurons
         /          \
        /            \
       OOOOOOOOOOOOOOOO   output layer

         OOOOOOOOOOOO     hidden layer

              O           input layer

The reason for this is that the neurons in the center of the output layer
have no way of knowing about the dip, since they where maximally active
for a=0 and for a=1. So for a=0.5 they will be maximally active as well.

Learning a NN to predict the x value where the dip occures works for the
example given, but the function I'm working with is much more complex,
so representing the fuction by a piecewise linear function will not do.
Also, my c is a vector of about 50 values, but that should not make
a difference.

A different approach consists of designing a recurrent network (having
one input neuron and one output neuron) with a dynamic behaviour in time.
After setting the activation of the input neuron to c all neurons are
updated a number of times, each time yielding a different activation
of the output neuron because of the recurrent connections (temporal memmory).
The activation of the output neuron at time t should then be f(c,t).
I have, however, not found a single example of this approach anywhere.

So my questions are:

Does anyone know of a learning rule for this approach?

Does anyone have a suggestion on how to solve the problem described?

Please email, I'll summarize.

Marcel Nijman
nijmanm@prl.philips.nl
From: sef@sef-pmax.slisp.cs.cmu.edu
Newsgroups: comp.ai.neural-nets
Subject: NIPS*92 Tutorials
Date: 13 Oct 92 03:56:40 GMT
Article-I.D.: cs.Bw1KAH.2JH.1
Organization: School of Computer Science, Carnegie Mellon

Several people have recently asked me for info about the upcoming NIPS
conference.  I'm not sure why they're asking me, since I am not part of the
NIPS organizing group (though I will be running one of the post-NIPS
workshops).  However, I did save the announcements that Steve Hanson sent
to some other mailing lists, but not (I believe) to comp.ai.neural-nets.
Since I'm sure some people on this newsgroup will be interested, I'll post
them here.

If you have questions or need registrataion info, please note the address
at the end of this post.  I don't know the answers.

-- Scott

===========================================================================

                      NIPS*92 TUTORIAL PROGRAM
                         November 30, 1992

NEUROSCIENCE

       9:30 - 11:30  ``ASPECTS OF COMPUTATION WITH REAL NEURONS''

                        William BIALEK
                     NEC Research Institute 

       1:00 - 3:00 ``ADVANCES IN COGNITIVE NEUROSCIENCE''

                         William HIRST
                New School for Social Research

       3:30 - 5:30 ``CORTICAL OSCILLATIONS: 
               CURRENT EXPERIMENTAL AND THEORETICAL STATUS''

                       Christof KOCH
                         CalTech 

       9:30 - 11:30 ``BIFURCATIONS IN NEURAL NETWORKS''

                      Bard ERMENTROUT
                   Department of Mathematics
                    University of Pittsburgh

ARCHITECTURES, ALGORITHMS, AND THEORY


       9:30 - 11:30 ``LEARNING THEORY AND NEURAL COMPUTATION''

                         Les VALIANT
                  Computer Science Department
                      Harvard University

       1:00 - 3:00 ``STATISTICAL ACCURACY OF NEURAL NETWORKS''

                       Andrew BARRON
                    Statistics Department
                    University of Illinois

       3:30 - 5:30 ``LEARNING AND APPROXIMATION IN NEURAL NETWORKS''

                       Tommy POGGIO
              Brain & Cognitive Science & AI Lab
                           MIT


IMPLEMENTATIONS

       1:00 - 3:00 ``ELECTRONIC NEURAL NETWORKS''
                      Josh ALSPECTOR
                        Bellcore




All inquiries for registration to Conference, Tutorials or Workshop
should go to

	NIPS*92 Registration
	SIEMENS Research Center
	755 College Rd. East
	Princeton, NJ 08550

	phone 609-734-3383
	email kic@learning.siemens.com
From: tonya@casbah.acns.nwu.edu (Tonya Hill)
Newsgroups: comp.ai.neural-nets
Subject: Stuttgart Neural Network Simulator
Date: 13 Oct 92 15:56:49 GMT
Article-I.D.: news.1992Oct13.155649.5144
Organization: Northwestern University, Evanston Illinois.

I am looking to get the Stuttgart Neural Network Simulator running on the
alliant FX/2800 using FXC-2800 v1.3.00.
If anyone else has already gotten it to run could you please send me a
summary of any major patches you applied.

thanx in advance
tonya
From: own@castle.ed.ac.uk (O Morgan)
Newsgroups: comp.ai.neural-nets
Subject: Neural Networks in C++ book, code is buggy
Date: 16 Oct 92 16:04:33 GMT
Organization: Scottish Agricultural College


I've just received a copy of the book Neural Networks in C++ by Adam
Blum.  The accompanying code (5 1/4" disk of course) is buggy.  Does
anyone know if there are corrected versions of the code available on FTP
anywhere.  Preferably a version that compiles straightoff in MS C7
(which currently is not the case). 

Thanks to anyone who can help.

BTW you are thinking of buying the book, I found it very disapointing,
writen in a hurry and pretty shallow.  There is no proper reference to
explain the command and data file structures and there are no examples
for BP (on the disk).  Half the book is program listings, and the
accompanying SW doesn't compile.  As you'd expect for a product of this
quality, the price is sky high: uk#66 (~$100). 

Olly Morgan
--
----------------------------------------------------------------------------
 Olly Morgan @ Scottish Agricultural College,  Edinburgh EH9 3JG, Scotland
               Tel: (+44 31) 667 1041          E.Mail: O.Morgan@ed.ac.uk
----------------------------------------------------------------------------
Newsgroups: comp.ai.neural-nets
From: fernando@eemips.tamu.edu (Susith Rohana Fernando)
Subject: E-mail address of Michael A. Franzini
Organization: Texas A&M University
Date: Fri, 9 Oct 1992 17:34:07 GMT

Hi,

I wonder anybody knows how to contact Michael A. Franzini? I believe he was
with the Dept. of Computer Science at CMU around 1989. I don't know whether
he is still there or not. I prefer an e-mail address, but even a phone 
number would be really helpful. Thank you in advance.

Susith Fernando(fernando@eemips.tamu.edu)

Dept. of Electrical Engineering
Texas A&M University
College Station, Tx77840
Newsgroups: comp.ai.neural-nets
From: a8111624@william.ee.nctu.edu.tw (ANALOG course)
Subject: gg
Organization: EENCTU
Date: Mon, 12 Oct 1992 14:04:26 GMT

I am interesting about the ideas of neuro-fuzzy control,
Could anybody give me some suggestion to go ahead.....
:q