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Talk:Entropy: Difference between revisions
→This is not exactly "entropy". H is in bits/symbol.
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This article is confusing Shannon entropy with information entropy and incorrectly states Shannon entropy H has units of bits.
There are many problems in applying H= -1*sum(p*log(p)) to a string and calling it the entropy of that string. H is called entropy but its units are bits/symbol, or entropy/symbol if the correct log base is chosen. For example, H of 01 and 011100101010101000011110 are exactly the same "entropy", H=1 bit/symbol, even though the 2nd one obviously carries more information entropy than the 1st. Another problem is that if you simply re-express the same data in hexadecimal, H gives a different answer for the same information entropy. The best and real information entropy of a string is 4) below. Applying 4) to binary data gives the entropy in "bits", but since the data was binary, its units are also a true statistical "entropy" without having to specify "bits" as a unit.
Total entropy (in an arbitrarily chosen log base, which is not the best type of "entropy") for a file is S=N*H where N is the length of the file. Many times in [http://worrydream.com/refs/Shannon%20-%20A%20Mathematical%20Theory%20of%20Communication.pdf Shannon's book] he says H is in units of "bits/symbol", "entopy/symbol", and "information/symbol". Some people don't believe Shannon, so [https://schneider.ncifcrf.gov/ here's a modern respected researcher's home page] that tries to clear the confusion by stating the units out in the open.
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