10-03-2019, 08:47 AM
Entropy is just a single figure, and one has a better view if one looks at the entire distribution.
The single character entropy condenses the difference between a picture like this:
![[Image: cf_matth.gif]](http://www.voynich.nu/img/stats/cf_matth.gif)
and the case where all frequencies are equal, into a single number. More interestingly, the conditional character entropy condenses into a single number how the left and right squares of the following are different:
![[Image: ent_fig07.gif]](http://www.voynich.nu/img/stats/ent_fig07.gif)
Clearly, many different distributions will lead to the same entropy value. The detailed distribution is like a simplified 'fingerprint' of the language.
To convert the Voynich MS text to real Latin, it is not sufficient to increase the entropy by the relevant amount. The entire detailed distribution has to become similar.
The single character entropy condenses the difference between a picture like this:
and the case where all frequencies are equal, into a single number. More interestingly, the conditional character entropy condenses into a single number how the left and right squares of the following are different:
Clearly, many different distributions will lead to the same entropy value. The detailed distribution is like a simplified 'fingerprint' of the language.
To convert the Voynich MS text to real Latin, it is not sufficient to increase the entropy by the relevant amount. The entire detailed distribution has to become similar.