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Reference details

Author(s) Year Title Reference View/Download

Les Hatton , Greg Warr

2017d

Information Theory and the Length Distribution of all Discrete Systems

WEBCanonicalLengthDistributions_10-07-2017.pdf

Synopsis and invited feedback

Peer review is important and acquiring competent reviewers is becoming a major problem for the journals today so I will be very happy to include constructive comment (positive or negative) with acknowledgement. If I am not competent to judge your commentary I will try and find somebody who is.

If you would like to provide feedback just e-mail me here.

Synopsis Invited Feedback Importance (/10, author rated :-) )
A milestone in academic publishing - possibly the first paper in history to be rejected by arXiv for "insufficient original or substantive research", all within a couple of hours of submission !

They must be quick readers. Its a detailed description (70 pages, 54 figures, 70 references, 5 appendices, 14 R analyses and a lot of equations) of a theory of ergodic information conservation which is able to predict the Canonical length distribution and alphabet distribution of a wide class of discrete systems at all scales.

This is applied to both Proteins and Computer Programs where it predicts with very strong statistical support that their length distribution is sharply unimodal, transitioning into an extraordinarily accurate power-law. In Music, it shows the same distribution and also predicts again with very strong statistical support that however we categorise such systems (for example categorising notes with and without duration), the categories are also power-laws of each other. In Texts, it is able to predict not only the observed Zipf's law of rank ordered word frequency but also the length distribution of words, (which obey the same distribution as Proteins and Computer Programs). Finally, it predicts the power-law behaviour of the distribution of Elements in the Universe (and also in sea-water).

We invite you to make your own mind up. If you want to criticise it, please feel free and tell us but you are then under the normal scientific obligation to prove why the theory is incorrect and to explain why the predictions are so accurate across so many different systems. On the other hand, if you think its interesting and as important as we do, please share it with your colleagues.

The journals certainly aren't interested.

Thanks.
None yet10

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Auto-generated: $Revision: 1.59 $, $Date: 2017/01/22 21:28:03 $, Copyright Les Hatton 2001-