Vision processing would suit it perfectly, however, neural networks,IIRC
even trained ones still need to vary the program,(if I'm wrong please
somebody correct me) although it is less of a major change after the
training is done, it is still an adaptive system, machine vision , image
recognition, encryption and crypto cracking etc are all computationally
intensive and the program doesn't change and thus, fit perfectly.

> -----Original Message-----
> From: pic microcontroller discussion list
> [mailto:PICLIST@MITVMA.MIT.EDU]On Behalf Of D. Jay Newman
> Sent: Friday, 28 March 2003 2:37 AM
> To: PICLIST@MITVMA.MIT.EDU
> Subject: Re: [EE]: FPGA computers
>
>
> I'm wondering if they'd be good for a neural network. It sounds
> like I could put a "trained" neural network onto an FPGA.
>
> Would they be better than a DSP for specialized vision processing
> (as in preprocessing and image for robotics)?
>
> > I can see them being extremely useful for cryptographic work.  It's the
> > ability to prototype hardware, but for computer scientists who don't
> > want to deal with the actual implementation.
> >
> > -Adam
> >
> > Micro Eng wrote:
> >
> > > OK...had to read thru all the comments and then add my own.
> > >
> > > First off....there are some correct assumptions...doing things in
> > > hardware,
> > > specific tasks for instance that are the ONLY task it does, as in
> > > graphics
> > > rendering do VERY well in hardware.  I've done it in my past life.
> > >
> > > Second, using them as a pre or co processor also does
> > > well....IF....again,
> > > its doing a specific task only.  And it still applies to cluster
> > > computers
> > > as well.
> --
> D. Jay Newman          ! Pudge controls the weather.
> jay@sprucegrove.com    !
> http://enerd.ws/~jay/  ! Oh good. My dog found the chainsaw.
>
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