HDTenEightyP/NetNews huggingface dataset:
From: icrosby@romulus.Reed.Edu (Ian Bradford Crosby)
Newsgroups: comp.multimedia
Subject: Re: 11hz sampling rate?  what planet are you on?
Date: 23 Nov 92 21:48:23 GMT
Article-I.D.: reed.1992Nov23.214823.935
Reply-To: Sam
Organization: Reed College, Portland, OR

In article <1992Nov23.011002.21654@seas.gwu.edu> thail@seas.gwu.edu  
(Samuel R. Posten) writes:
> 11 hz sampling rate? on a sb pro, sorry, but my sb pro can sample 22khz  
in
> stereo.  you are thinking of the old sb card.
> 
> BTW, evil plug!!!!
> 
> Egghead software is selling the multimedia startup kit for $398.00
> you get sb pro basic
> internal cd rom
> ms Bookshelf.
> 
> If there is no egghead near you call 1-800 egghead, they can help you  
out.
> 
> Sam
22 kHz at 16 bits?  I doubt it.  Also, the SB Pro Basic doesn't have a  
MIDI interface or a SCSI interface.  The PAS sound card is superior by an  
order of magnitude.  That's why I'm so keen on finding out where Mr.  
Simonoff in New York is getting the Media Fusion pack for $399.  It  
contains the PAS 16-bit card, and if it actually has an NEC CD-ROM player  
in it, even if it ships without any bundled software, it's a hell of a  
deal.
	Ian Crosby
	icrosby@romulus.reed.edu
Newsgroups: comp.multimedia
From: s1369046@techst02.technion.ac.il (Ophir Prusak)
Subject: Controller card for One-frame-recorder
Reply-To: s1369046@techst02.technion.ac.il (Ophir Prusak)
Organization: Technion, Israel Inst. of Technology
Date: Sun, 22 Nov 1992 13:25:23 GMT

 I am looking for a controller for a professional video-tape-recorder
that can do one-frame-at-a-time recording. I DONT know much more than this
( the request is for a friend ) Any help would be most appreciated.
please reply by e-mail.

Thanx in advance,
Ophir
s1369046@t2.technion.ac.il
Newsgroups: comp.ai
From: kaykit@iti.gov.sg (Chan Kay Kit (KSL))
Subject: Seeking email/postal address of ....
Reply-To: kaykit@iti.gov.sg
Organization: Information Technology Institute, National Computer Board, S'pore
Date: Tue, 17 Nov 1992 02:36:34 GMT

Hello everyone,

	I need help in finding either the

	(i) email address or
	(ii) postal address

of any one of the following persons:

	(i) Steven A. Harp
	(ii) Tariq Samad
	(iii) Aloke Guhua

They coauthored a paper entitled "Designing Application-Specific Neural Networks
Using the Genetic Algorithm" ,which appeared in NIPS II. The most recent postal
address I've got is

	Honeywell SSDC
	1000 Boone Avenue North
	Golden Valley, MN 55427

which I've been told is no longer valid.

Would appreciate any info I can get. Please email all replies to kaykit@iti.gov.sg.

Thanks!



---
Kay-Kit CHAN    			| Internet: kaykit@iti.gov.sg
Knowledge Systems Lab			| Bitnet:   kaykit@itivax
Information Technology Institute	| Tel:      (65) 772-0920
National Computer Board of Singapore    | Fax:      (65) 770-3043
From: rosenb@bimacs.BITNET (rosenberg erel)
Newsgroups: comp.ai
Subject: Looking for Expert System Shall
Date: 17 Nov 92 14:25:47 GMT
Reply-To: rosenb@bimacs.UUCP (rosenberg erel)
Organization: Bar-Ilan University, Israel.


        Request for Information

I'm looking for an expert system shall under $1000.

The requirement for the Expert System shall are:

a. Rule based shall.

b. Interface to C (or C++)

c. Dos platform. (Windows and Unix option will be helpful)

Please use E-Main for replay.


                                                Ere'l Rosenberg
                                                Bar-Ilan University

                                                rosenb@bimacs.cs.biu.ac.il
Newsgroups: comp.ai
From: hao@orca.micro.umn.edu (Hao Chen)
Subject: NN in public domain
Organization: University of Minnesota, Minneapolis: Under Grad Workstation Lab.
Date: Fri, 20 Nov 1992 22:41:51 GMT

hello --

I was wondering what Neural Networks are available via ftp -- with emphasis
on networks that change both their architectures AND their weights... 

Thanks a lot!

hao chen

(Email Preferred but not essential)...
From: bat@dstos3.dsto.gov.au
Newsgroups: comp.ai.neural-nets
Subject: The Military and Neural Networks ??
Date: 19 Nov 92 11:49:47 CST
Organization: Defence Science and Technology Organisation

I am probably asking the impossible here, but here goes anyway
                                                             
                                           
Has anyone any experience with assessing neural networks for defence
applications ? 

Does such a thing as a  mil spec for Neural Networks exist or is one being 
developed ?

How interested/receptive are the military in Neural technology ? I know that
money is being poured into research , but does this ever actually get beyond 
the research stage. IE are they  brave/confident enough with the technology 
to allow it to see service or is it still largely at the 
"just keeping our noses in" stage.

My reasons for wanting to know are largely commercial. I am trying to decide
whether or not to invest the time and effort and money into developing a
neural engine.
						Brenton Thomas 


Thanking you in advance.

Newsgroups: comp.ai.neural-nets
From: wgliou@iastate.edu (Weih-Guang W Liou)
Subject: NN to find roots
Summary: How to use NN to find roots of polynimial ?
Organization: Iowa State University, Ames IA
Date: Fri, 20 Nov 1992 02:12:22 GMT

Hi,

  I am wondering can we use NN to find roots of a polynomial ?
( or some way to find eigen-value of a matrix ).

  Possible or not .

  Liou at Ames.
From: 738mathers@gw.wmich.edu
Newsgroups: comp.ai.neural-nets
Subject: Euchre implementations?
Date: 23 Nov 92 19:53:09 EST
Organization: Western Michigan University


I am trying to get a net to learn how to play the game of Euchre.
I was wondering if anybody has tried it before, or if anyone can
make possible recommendations.

Thanks!


Newsgroups: comp.ai.neural-nets
From: rs69@cunixb.cc.columbia.edu (Rong Shen)
Subject: FTP sites for models
Organization: Columbia University
Date: Sat, 21 Nov 1992 22:16:23 GMT

Hello:

	Can anyone tell me from which ftp site I can get an example of
the backpropagation or ART2 (ART*) model?

	Thanks.
--
rs69@cunixb.cc.columbia.edu
From: bnns93@cs.bham.ac.uk (British Neural Network Society)
Newsgroups: comp.ai.neural-nets
Subject: BNNS Meeting (UK) - *change of date*
Date: 23 Nov 92 15:54:33 GMT
Organization: School of Computer Science, University of Birmingham, UK

CHANGE OF DATE

The BNNS Symposium will now be on the 29th January 1993 and not the 3rd
February 1993.

Apologies for any inconvenience caused.

Registration details available very shortly - watch this space.

Russell Beale.
From: 00cewhetston@leo.bsuvc.bsu.edu
Newsgroups: comp.ai.neural-nets
Subject: Neural Net Opinions
Date: 19 Nov 92 17:37:00 GMT
Organization: Ball State University, Muncie, In - Univ. Computing Svc's

Are you or your company currently using a form of neural networks?  What are
your feelings about these systems?  Please E-Mail your replies.  Thanks.
From: frandsen@seismo.CSS.GOV (Marvin Vaun Frandsen)
Newsgroups: comp.ai.neural-nets
Subject: Re: The Military and Neural Networks ??
Date: 20 Nov 92 02:03:20 GMT
Organization: Center for Seismic Studies, Arlington, VA

I will take a stab at a couple of your questions.

Neural nets are used in various military applications.  Automatic target
recognition, or automatic waveform recognition are two obvious uses.  

Some uses are purely R&D.  Others are in working prototypes, i.e. one-of-a
kind (or very few) devices that are not in full scale production for one
reason or another.

I am not aware of any mil standard for neural nets as such.  With projects
I am familiar with, the statement of work specifies what is needed to be
done and the contractor proceeds to implement the bottom line performance
desired.  This however is in the R&D arena, though again the prototypes
may be useful.

Hope that helps.

--Marv Frandsen         
     
         Air f
From: pd_s001@ceres (J Karwatzki)
Newsgroups: comp.ai.neural-nets
Subject: Re: help
Date: 20 Nov 1992 09:42:56 GMT
Organization: Kingston University
NNTP-Posting-Host: ceres.kingston.ac.uk
X-Newsreader: Tin 1.1 PL4

sc@basil.eng.monash.edu.au (Cong Shiguo) writes:
: Hello, 
: 
: 	I am tring to train a neural network controller. I met a problem
: which I don't know how to solve it.  In controller cases, we must train the 
: neural nets to follow the desired outputof the plant to controlled. The 
: reference input to the system can be any time-varying signals, such as step 
: function or sinusoidal waveform with different frequencies. My question is 
: What kind of signal can be used as training reference? I tried to use step 
: input and white noise. The nn controller works well to its training reference
: but doesn't converge to those it didn't learn.
: 
: 	Could anybody give me some help please? Many thanks.
: 
: 
: 
--
Such an approach will only be useful if all inputs to the system can be 
categorised and, hence, taught to a neural network. Since this is
extremely unlikely in most cases the nn approach is probably not suited
for such an application. What may be much more useful would be the ability
to categorise disturbances to the plant. A nn could be taught to 
recognise typical disturbances (ignoring others) and take appropriate
corrective action as they occur.
John Karwatzki
Kingston University
Kingston
Surrey
UK
karwatzki@kingston.ac.uk
Newsgroups: comp.ai.neural-nets
From: sc@basil.eng.monash.edu.au (Cong Shiguo)
Subject: help
Keywords: Neural network controller
Organization: Electrical & Computer Systems Eng. Dept., Monash Uni.
Date: Mon, 16 Nov 1992 23:07:20 GMT

Hello, 

	I am tring to train a neural network controller. I met a problem
which I don't know how to solve it.  In controller cases, we must train the 
neural nets to follow the desired outputof the plant to controlled. The 
reference input to the system can be any time-varying signals, such as step 
function or sinusoidal waveform with different frequencies. My question is 
What kind of signal can be used as training reference? I tried to use step 
input and white noise. The nn controller works well to its training reference
but doesn't converge to those it didn't learn.

	Could anybody give me some help please? Many thanks.


	
Newsgroups: comp.ai.neural-nets
From: srctran@world.std.com (Gregory Aharonian)
Subject: Re: Reactive Keyboarding
Organization: The World
Date: Wed, 18 Nov 1992 22:27:07 GMT

With regards to Reactive Keyboards and neural networks, Hitachi just won
a US patent, # 5,163,111, titled "Customized personal terminal device"
which uses neural networks to allow you to have a Reactive Workstation,
so to speak.  If there is any money in it, Hitachi has the patent.

Greg Aharonian
-- 
**************************************************************************
Greg Aharonian
Source Translation & Optimiztion
P.O. Box 404, Belmont, MA 02178
Newsgroups: comp.ai.neural-nets
From: wm@spcklx.mpifr-bonn.mpg.de (Wolfgang Mauder)
Subject: PD software for genetic optimization
Organization: Max-Planck-Institut f"ur Radioastronomie
Date: Mon, 16 Nov 1992 14:31:35 GMT

I am looking for references and for PD software for function optimization using genetic algorithms. Who can help?

Thank you



Wolfgang Mauder
MPIfR
Bonn

Newsgroups: comp.ai.neural-nets
From: evol@infko.uni-koblenz.de
Subject: Backpercolation vs. other training algorithms
Organization: University of Koblenz, Germany
Date: Tue, 17 Nov 1992 15:20:07 GMT


I am working on a technical report comparing many different training
algorithms for feedford networks. All algorithms are applied to a
very hard to solve classification task. Up to now I have applied
the following algorithms:

	1. Standard Backprop
	2. Standard Backprop in batched mode
	3. Standard Backprop in batched mode, learning rate
	   set by Harry A. C. Eaton and Tracy L. Olivier's rule
	4. Standard Backprop  with decreasing learning rate
	   (Christian Darken and John Moody)
	5. J. Schmidhuber's adaptation of the step size
	6. R. Salomon's evolutionary adaptation of the learning rate
	7. L.-W.Chan and F. Fallside 's adaptation of the learning rate
	   by angle observing
	8. A.H. Kramer and A. Sangiovanni-Vincentelli's Polak-Ribiere
	   method with line search
	9. J. Leoard and M.A. Kramer's conjugate gradient method
	   with line search
	10. F.M. Silva and L.B. Almeida's learning rate adaptation
	    by detecting sign changes in the derivatives
	11. T. Tollenaere's SuperSAB
	12. M. Riedmiller's RPROP
	13. Robert A. Jacobs Delta-Bar-Delta technique
	14. Scott E. Fahlman's Quickprop

I am still looking for some more training algorithms. I have tried to
implement BACKPERCOLATION. Nervertheless the only report on backpercolation
I know is not sufficient to implement this algorithm. Does anyone know a
good paper on backpercolation? Has anyone applied it to bigger problems ?
Is there a public available implementation (other than SNNS) ? 

By the way RPROP and Quickprop are clearly the winners. I will publish
my report soon (available by ftp).

	Thanks in advance

		Randolf Werner


Newsgroups: comp.ai.neural-nets
From: block@dxlaa.cern.ch (Frank Block)
Subject: Re: The Military and Neural Networks ??
Reply-To: block@dxlaa.cern.ch (Frank Block)
Organization: CERN, European Laboratory for Particle Physics, Geneva
Date: Thu, 19 Nov 1992 08:59:24 GMT


In article <1992Nov19.114948.165175@dstos3.dsto.gov.au>, bat@dstos3.dsto.gov.au writes:
|> Organization: Defence Science and Technology Organisation
|> 
|> I am probably asking the impossible here, but here goes anyway
|>                                            
|> Has anyone any experience with assessing neural networks for defence
|> applications ? 

I only hope there are not too many with the kind of experience you're asking
for...

|> 
|> Does such a thing as a  mil spec for Neural Networks exist or is one being 
|> developed ?

Sorry, but what is a 'mil spec'? Something like specification for military
applications? Since I'm non-American and non-military I don't know the slang.

|> 
[...]
|> 
|> My reasons for wanting to know are largely commercial. I am trying to 
|> decide whether or not to invest the time and effort and money into 
|> developing a neural engine.
|> 						Brenton Thomas 
|> 

I would suggest you invest your 'the time and effort and money' into something
which is really worth it. What about some applications of Neural Networks in 
medicine?

|> 
|> Thanking you in advance.
|> 
|> 

You're always welcome.

Frank
--

===============================================================================
Frank Block
Div. PPE				
CERN - European Laboratory for Particle Physics
CH-1211 Geneve 23					BLOCKF@cernvm.cern.ch
Switzerland						BLOCKF@vxcern.cern.ch
===============================================================================
Newsgroups: comp.ai.neural-nets
From: freek@phil.ruu.nl (Freek Wiedijk)
Subject: Where can I buy `MacBrain'?
Organization: Department of Philosophy, University of Utrecht, The Netherlands
Date: Sun, 22 Nov 1992 21:41:50 GMT

We (the departement of Philosophy at the University of Utrecht) want to
purchase the program called `MacBrain' (if it's not _too_ expensive).
I understand it's a neural net simulator.

Questions:
	Where do I order it?
	How much will it cost?
	How long will it take to be delivered?
	On what Macs will it run?
	What's the current version?

I supposed this to be in the FAQ, but I couldn't find it in there.

Freek
--
Third theory of Phenomenal Dynamics:  The difference between a symbol
and an object is quantitative, not qualitative.
Newsgroups: comp.ai.neural-nets,uw.neural-nets
From: tim@gold.iss.nus.sg (Tim Poston)
Subject: Re: How deep are spurious attractor basins?
Keywords: Hopfield, Boltzmann, Attractors, Energy Functions
Reply-To: tim@iss.nus.sg (Tim Poston)
Organization: Institute of Systems Science, NUS, Singapore
Date: Fri, 20 Nov 1992 06:42:20 GMT

In article <Bxv79K.G7F@watserv1.uwaterloo.ca> joordens@watserv1.uwaterloo.ca (Steve Joordens) writes:

> However, I 
>have heard that this may not be the case (i.e., that spurious attractors
>may be as deep as learned attractors).

If "as deep as" means "a sum-of-squared errors that is just as low",
it also surely means "as good as".
In this case, what is "spurious" about such attractors?

If you have a better function for measuring goodness,
use it in learning.

Tim


___________________________________________________________________
	    My lucky number is irrational.
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
Newsgroups: comp.ai.neural-nets
From: hm@cs.brown.edu (Harry Mamaysky)
Subject: PhD programs in Learning
Organization: Somewhere East or Somewhere West
Date: Mon, 16 Nov 1992 16:55:40 GMT

Howdy all,

I am a Master's student at Brown University. I expect to be graduating
towards the end of 1993. I am very seriously considering getting a PhD
in the area of machine learning, with a strong cognitive science
emphasis. So, I am looking around for schools which have programs in
this area. Among particular concerns of mine are the following:

	1. Since, I will have an M.S., I want a program that will
	not require me to take the usual year of courses that PhD
	students need, since I will have already done so.

	2. I would like a program which places a strong emphasis on
	doing things in a bilogically feasible way, in other words
	one with a cognitive science flavor. If the program also dealt
	with actual real world applications of learning methods, that
	would be a big plus.

	3. I am particularly interested in connectionist learning,
	and especially with maintaining domain information in such
	a context.

	4. Also, if I could somehow have my Master's thesis fulfill
	a part of the research requirement for a PhD that would be 
	nice.

	5. Of course, I would like to find a school with a strong
	research program and a strong faculty.

Thanks in adavance for all responses. I would prefer email, but any
sort of a response would be much appreciated.

Harry.

hm@cs.brown.edu
Xref: sparky comp.ai.neural-nets:4299 sci.engr:2289 sci.engr.control:285
From: ptennebo@cs.strath.ac.uk (Per O Tennebo Info Eng 3)
Newsgroups: comp.ai.neural-nets,sci.engr,sci.engr.control
Subject: Looking for ultrasonic data
Summary: Using neural networks for analysis of ultrasonic data
Keywords: ultrasonic, testing, NDT
Date: 17 Nov 92 18:07:44 GMT
Organization: University of Strathclyde, Glasgow, Scotland


Hello,

        I'm trying to use neural nets for noise filtering and
classification of ultrasonic data. However, there's one big problem:

        Most companies are _very_ reluctant to release any data, revealing
all the flaws they find in our nuclear power stations, submarines, etc.
So - to the point: does anybody know of any databases out there
with (real or simulated) ultrasonic data?


        Thanks -- Per

-- 
Newsgroups: comp.ai.neural-nets
From: yair@siren.arc.nasa.gov (Yair Barniv)
Subject: NIPS program
Reply-To: grendel@windchime.arc.nasa.gov
Organization: NASA Ames
Date: Mon, 23 Nov 1992 19:23:19 GMT

Hi guys.
Anyone can send me the NIPS program email announcement.
to        
         yair@windchime.arc.nasa.gov

Thanks, Yair  
Newsgroups: comp.ai.neural-nets,comp.ai
From: clin@eng.umd.edu (Charles Lin)
Subject: Help need with hybrid NN/ES systems
Date: Sat, 21 Nov 92 22:48:38 GMT
Organization: College of Engineering, Maryversity von Uniland, College Park
Originator: clin@periodic.eng.umd.edu



    The news server is acting funny, so my original attempt at posting
seems to have failed.

    I am interested in finding any work done on hybrid systems which
combine neural networks and expert systems or any other knowledge
(symbolic) based systems.   If anyone has references, or know of anyone
working in the area, please send me address, phones, or e-mail addresses.
Send info to clin@eng.umd.edu.

    Also, I am looking for an M.E. Ulug, who seems to have done work
in this area.   He may be working at GE in Schenectady, NY.   If anyone
has his e-mail address, please let me know.   Thanks.

--
Charles Lin
clin@eng.umd.edu
From: hughp@essex.ac.uk
Newsgroups: comp.ai.neural-nets
Subject: brendt@za.ac.uct.ee.dip1 ??????
Date: 16 Nov 92 17:38:47 GMT
Reply-To: hughp@essex.ac.uk ()
Organization: University of Essex, Colchester, UK

Could brendt@za.ac.uct.ee.dip1 ??

mail hughp@uk.ac.essex or
     hughp@155.245.10.133

as I cannot seem to email you back. Everything
I try bounces back. 

Could you send me your internet number ?

I was most interested in your mail.
Newsgroups: comp.ai.neural-nets
From: karun@faline.bellcore.com (N. Karunanithi)
Subject: Where to find?
Reply-To: karun@faline.bellcore.com (N. Karunanithi)
Organization: Bellcore MRE
Date: Mon, 23 Nov 92 14:41:35 GMT

Newsgroups: comp.ai.neural-nets
From: stevew@syma.sussex.ac.uk (Steve Williams)
Subject: Help wanted for coarse coding scheme.
Organization: University of Sussex
Date: Tue, 17 Nov 1992 14:51:55 GMT

I am doing some research into the possibilities of a SRN (Simple Recurrent
Network) being useful as a psychological model of the object concept. Details
of this aide I have run into rather a tricky problem, namely, how to transform
a spatial array cointaining the 2d coordinates of a single object, into the
three coordinates specifying the location of the object in a coarse coding
scheme. I have considered generating a look up table in a 3d array which maps
onto the 2d spatial array but this would be cumbersome to code and not as
flexible as I would like - I would have to alter the contents of the look up
table everytime I adjusted the size of the network and thus its receptive
field. If anyone has any ideas then I would be interested to know them. If you
require any furthur information then please e-mail me at my Janet address, as
this explanation of the situation is a little compact!

Thanks in advance,
Steve Williams (e-mail: stevew@uk.ac.sussex.epunix or
stevew@uk.ac.sussex.syma)
Newsgroups: comp.ai.neural-nets
From: lvh@jhunix.hcf.jhu.edu (Larrie Hutton)
Subject: Neural networks and graduate schools in physics
 
Keywords: neural networks, graduate schools, physics
Organization: HAC - Johns Hopkins University, Baltimore
Date: Thu, 19 Nov 1992 05:48:38 GMT


I have had several students ask about physics departments
that offer graduate programs with a neural networks emphasis.
If your school is one such reply to me by e-mail and I will
summarize. 

.
w

Newsgroups: comp.ai.neural-nets
From: mike@psych.ualberta.ca (Mike Dawson)
Subject: Re: Neural Nets and Visual tracking?
Organization: Psychology, University of Alberta, Edmonton
Date: Mon, 16 Nov 1992 18:50:03 GMT

The following article describes a connectionist network for tracking
objects (i.e., solving the motion correspondence or tag-assignment
problems), though this network doesn't "anticipate".  The article
also reviews object tracking in the context of visual neuroscience.

Dawson, M.R.W. (1991).  The how and why of what went where in apparent
	motion:  Modeling solutions to the motion correspondence problem.
	Psychological Review, 98, 569-603.
--
Michael R.W. Dawson                       email: mike@psych.ualberta.ca
Biological Computation Project, Department of Psychology
University of Alberta, Edmonton, AB CANADA T6G 2E9
Tel:  +1 403 492 5175   Fax: +1 403 492 1768