# Shannon entropy

## EnglishEdit

### EtymologyEdit

Named after Claude Shannon, the "father of information theory".

### NounEdit

Shannon entropy (countable and uncountable, plural Shannon entropies)

1. information entropy
Shannon entropy H is given by the formula ${\displaystyle H=-\sum _{i}p_{i}\log _{b}p_{i}}$  where pi is the probability of character number i showing up in a stream of characters of the given "script".
Consider a simple digital circuit which has a two-bit input (X, Y) and a two-bit output (X and Y, X or Y). Assuming that the two input bits X and Y have mutually independent chances of 50% of being HIGH, then the input combinations (0,0), (0,1), (1,0), and (1,1) each have a 1/4 chance of occurring, so the circuit's Shannon entropy on the input side is ${\displaystyle H(X,Y)=4{\Big (}-{1 \over 4}\log _{2}{1 \over 4}{\Big )}=2}$ . Then the possible output combinations are (0,0), (0,1), and (1,1) with respective chances of 1/4, 1/2, and 1/4 of occurring, so the circuit's Shannon entropy on the output side is ${\displaystyle H(X{\text{and}}Y,X{\text{or}}Y)=2{\Big (}-{1 \over 4}\log _{2}{1 \over 4}{\Big )}-{1 \over 2}\log _{2}{1 \over 2}=1+{1 \over 2}=1{1 \over 2}}$ , so the circuit reduces (or "orders") the information going through it by half a bit of Shannon entropy due to its logical irreversibility.