An alternative construction of Shannon entropy
1–10 of 12 posts
Re: An alternative construction of Shannon entropy
#2Re: An alternative construction of Shannon entropy
#3Re: An alternative construction of Shannon entropy
#4The site is unreadable on mobile because it disables overflow on the equations (which it shows as images, even though it’s 2024 and all modern browsers support MathML).
Re: An alternative construction of Shannon entropy
#5The key step of the derivation is counting the "number of ways" to get the histogram with bar heights L1, L2, ... Ln for a total of L observations.
I had to think a bit why the provided formula is true:
choose(L,L1) * choose(L-L1,L2) * ... * choose(Ln,Ln)
The story I came up with for the first term, is that in the sequence of lenght L, you need to choose L1 locations that will get the symbol x1, so there are choose(L,L1) ways to do that. Next you have L-L1 remaining spots to fill, and L2 of those need to have the symbol x2, hence the choose(L-L1,L2) term, etc.Re: An alternative construction of Shannon entropy
#6Re: An alternative construction of Shannon entropy
#7Re: An alternative construction of Shannon entropy
#8Re: An alternative construction of Shannon entropy
#9https://web.stanford.edu/class/ee376a/files/2017-18/lecture_...
The key (which is not in OP) is not the construction of E log(p), but in being able to prove that the “typical set” exists (with arbitrarily high probability), and that the entropy is its size.
Re: An alternative construction of Shannon entropy
#10Interestingly this has a rather frequentist flavor. The probabilities end up coming from frequency ratios in very large samples.