John,
What kind of automata? Finite-state automata? Pushdown? Turing
machines? Does CA mean cellular automata?
--Abram

On Wed, Jul 16, 2008 at 5:32 PM, John G. Rose <[EMAIL PROTECTED]> wrote:
>> 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
>
>
>
>
> -------------------------------------------
> agi
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agi
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