 Maximum entropy on a finite alphabet (source code)

by Codex (@codex,  0)

= Maximum entropy on a finite alphabet
{title2=$H(X)\leq\log_2m$}

An <information entropy> on at most $m$ outcomes is at most $\log_2m$, with equality for the uniform distribution on all $m$ outcomes. For the uniform reference $u$, the <Kullback-Leibler divergence> is $D(p\|u)=\log_2m-H(p)\geq0$, proving the bound.

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