Algorithm that makes maximum compression of completly diffused data.

[jonas.thornvall at gmail.com]

Den onsdagen den 30:e oktober 2013 kl. 20:46:57 UTC+1 skrev Modulok:
> On Wed, Oct 30, 2013 at 12:21 PM,  <jonas.t... at gmail.com> wrote:
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> I am searching for the program or algorithm that makes the best possible of completly (diffused data/random noise) and wonder what the state of art compression is.
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> I understand this is not the correct forum but since i think i have an algorithm that can do this very good, and do not know where to turn for such question i was thinking to start here.
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> It is of course lossless compression i am speaking of.
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> --
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> https://mail.python.org/mailman/listinfo/python-list
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> 
>  
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> >> I am searching for the program or algorithm that makes the best possible of
> >> completly (diffused data/random noise) and wonder what the state of art
> 
> >> compression is.
> 
> 
> None. If the data to be compressed is truly homogeneous, random noise as you
> describe (for example a 100mb file read from cryptographically secure random
> 
> bit generator such as /dev/random on *nix systems), the state-of-the-art
> lossless compression is zero and will remain that way for the foreseeable
> 
> future.
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> There is no lossless algorithm that will reduce truly random (high entropy)
> data by any significant margin. In classical information theory, such an
> 
> algorithm can never be invented. See: Kolmogorov complexity
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> Real world data is rarely completely random. You would have to test various
> 
> algorithms on the data set in question. Small things such as non-obvious
> statistical clumping can make a big difference in the compression ratio from
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> one algorithm to another. Data that might look "random", might not actually be
> random in the entropy sense of the word.
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> 
> >> I understand this is not the correct forum but since i think i have an
> >> algorithm that can do this very good, and do not know where to turn for such
> 
> >> question i was thinking to start here.
> 
> 
> Not to sound like a downer, but I would wager that the data you're testing your
> 
> algorithm on is not as truly random as you imply or is not a large enough body
> of test data to draw such conclusions from. It's akin to inventing a perpetual
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> motion machine or an inertial propulsion engine or any other classically
> impossible solutions. (This only applies to truly random data.)
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> 
> -Modulok-

My algorithm will compress data from any random data source.