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From: ddturner@kocrsv01.delcoelect.com
Subject: Re: hardware implementation of a neural network 
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In article <parkCyIFD9.EAo@netcom.com>, <park@netcom.com> writes:
> In article <38r1jp$6ga@sol.sun.csd.unb.ca> you write:
> 
> > I am going to implement a neural network controller in hardware for a
> > prosthetic arm. I am just starting out and am looking for dedicated
> > hardware that could do this. Does anyone know who I could contact or
> > know what devices (chips) I could use?
> > 
> > Willem J. Atsma
> > Institute of Biomedical Engineering
> > University of New Brunswick, Canada
> > e-mail: r7kf@unb.ca
> 
> Intel developed two neural net chips, but for some reason seems to
> have licensed distribution rights to two other companies.
> 
> 	Ni1000 Recognition Accelerator, available only from Nestor ...
> 
> 		Cheryl Grove, Director of Sales and Marketing
> 		Embedded Systems
> 		Nestor, Inc.
> 		One Richmond Square
> 		Providence RI 02906
> 		(401)331-9640 tel
> 		(401)331-7319 fax
> 
> 	80170NX Electrically Trainable Analog Neural Network (ETANN),
> 	available only from ... 
> 
As I understand it, Intel is in charge of this one, but CSS makes brainmaker 
software that can download nets to it.

> 		California Scientific Software
> 		10024 Newton Road
> 		Nevada City, CA  95959
> 		(916)478-9040
> 		(800)284-8112 sales
> 		(916)478-9035 technical support
> 		(916)478-9041 fax
> 		(916)478-9042 bbs
> 
> 	Intel published a very informative 42-page data booklet on it:
> 
> 	80170NX Electrically Trainable Analog Neural Network
> 	Order number 290408-003, March 1993.
> 
> 	The front page of this booklet carries the word "experimental."
> 
> National Semiconductor offers the NeuFuz fuzzy logic development
> system, which delivers executable code for National's COP8 family of
> 8-bit microcontrollers.
> 
> 	Naveed Khan
> 	National Semiconductor
> 	Intelligent Systems Group
> 	2900 Semiconductor Drive
> 	P.O. Box 58090, M/S E-255
> 	Santa Clara, CA  95052-8090
> 	(408)732-6107 FAX
> 
> My copy of the NeuFuz brochure is also dated March 1993, and carries
> the word "preliminary" on its front page.

National Semiconductors product is EXTREMELY limited.  As I recall, it can have 
only four inputs.  We tried it on a simple problem and couldn't get it to 
work.  It's hardly more than a toy in my opinion.

> 
> The Hecht-Nielsen Company (San Diego, CA) offers a coprocessor board,
> but I think it's based on a conventional digital signal processing
> chip such as the Intel i860.  Still, most of the processing in an
> artificial neuron is just multiply-and-accumulate, which DSPs are
> really good at.  I suppose you could even evaluate the nonlinear
> "squashing" function as a table look up in a way that is also
> well suited to the DSP's abilities.  
> 
> Neural Semiconductor (Carlsbad, CA) claims that its NU32/SU3232 neural
> net chip can process 100,000 patterns (not connections) per second.

This company does not exist anymore, as far as I can tell.  However, Hughes 
bought the rights to develop there parts (They didn't exist before Hughes got 
on board.).  Hughes did develop the parts, but the last time I checked, they 
didn't have any development software or hardware for them.  Neural 
Semiconductor was suppose to write/design it.  Hughes wasn't able to get hold 
of them.

> 
> Inmos' Transputers (made in the U.K.) are frequently used to implement
> neural networks.  Nestor used to sell the German Hema Transputer
> board, and may still.
> 
> Motorola, NEC, and Fujitsu were also reported to be developing neural
> network chips a bout 5 years ago.  I don't know if any of them got to
> market.
>

Motorola has a part soon to be out called the Association Engine.  It is highly 
flexible and is the best neural net chip I have seen to date.

> 
> Note that you generally need the fancy hardware most for training,
> since that involves about three passes over a neuron per example,
> while using a trained net without learning only requires a single
> pass.  That's assuming your are using a simple freedforward network,
> not one of the more exotic nets -- Hopfield, ART, etc. -- that
> implement a dynamic process, so that you have to woit for the data to
> make many passes through each neuron before the net settles down
> enough for you to read out an answer.  Also, training requires
> processing large numbers of examples -- often thousands or tens of
> thousands -- and the main reason you need speed then is so you don't
> have to twiddle your thumbs in the lab for hours to see if the damned
> thing is going to learn or not this time.  In your application, the
> chip will only have to process data at the rate determined by the
> dynamics of the prosthetic arm.  You may find that a quite modest
> processor -- even an ordinary microprocessor -- will do the job
> nicely, even if you find you need a $50,000 workstation with a special
> purpose neural net coprocessor board to train on.  You may also find
> you can use multiple chips working in parallel in the arm, further
> decreasing throughput requirements for any one chip.
> 
> You will probably want a military quality rating on any equipment you
> plan to field.  Professor Steven Jacobsen at the University of Utah
> (maybe at Nova Robotics, too) has been over that road several times.
> As I recall, he reported that one of his amputee testers took a shower
> wearing the Utah arm!
> 
> In my experience, glossy brochures prepared by a marketing deparment
> are rarely a good basis for an engineering decision.  I strongly
> recommend you get the detailed technical specifications on each
> neurochip you may use, then let your best wirehead study them and tell
> you what he thinks would be their pros and cons for use in the arm.
> And try to talk to other "satisfied customers" who are using the
> product in an application that is as close as possible to your own.
> 
> Best of luck,
> 
> Bill Park
> =========
> -- 
> Grandpaw Bill's High Technology Consulting & Live Bait, Inc.
					       ^^^^^^^^^
What's the going rate for night crawlers these days??? ;-)

Douglas D. Turner
Senior Electronics Design Engineer
Advanced Vehicle Systems
Delco Electronics Corporation
ddturner@kocrsv01.delcoelect.com

I am Homer of Borg.  Prepare to be Assimu.....OOO Doughnuts.....
