> From: Pei Wang [mailto:[EMAIL PROTECTED]
> On Mon, Jul 7, 2008 at 12:49 AM, John G. Rose <[EMAIL PROTECTED]>
> wrote:
> >
> > In pattern recognition, are some patterns not expressible with
> automata?
> 
> I'd rather say "not easily/naturally expressible". Automata is not a
> popular technique in pattern recognition, compared to, say, NN. You
> may want to check out textbooks on PR, such as
> http://www.amazon.com/Pattern-Recognition-Learning-Information-
> Statistics/dp/0387310738/ref=pd_bbs_sr_2?ie=UTF8&s=books&qid=1215382348&
> sr=8-2
> 
> > The reason is ask is that I am trying to read sensory input using
> "automata
> > recognition". I hear a lot of discussion on pattern recognition and am
> > wondering if pattern recognition is the same as automata recognition.
> 
> Currently "pattern recognition" is a much more general category than
> "automata recognition".
> 


I am thinking of breaching the gap somewhat with automata recognition + CA
recognition. So automata as in automata, semiautomata, and automata w/o
action + CA recognition. But recognizing automata from data requires some
techniques that pattern recognition uses. Automata are easy to work with,
especially with visual data, as I'm trying to get to a general pattern
recognition automata subset equivalent.

I haven't heard of any profound general pattern recognition techniques so
I'm more comfortable attempting to derive my own functional model. I suspect
how existing pattern classification schemes work as they are ultimately
dependant on the mathematical systems used to describe them. And the space
of all patterns compared to the space of all probable patterns in this
universe... 

I'd be interested in books that study pattern processing across a complex
systems layer... or in this case automata processing just to get a
perspective on any potential computational complexity advantages.

John




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