May 29, 2022 · Interpretation of Shannon Entropy formula as expected value Ask Question Asked 3 years, 7 months ago Modified 3 years, 7 months ago

Sep 14, 2018 · 39 To recover entropy, you have to consider a sequence of dice throws, and ask how many questions per roll you need in an optimal strategy, in the limit that the number of …

From this slide, it's said that the smallest possible number of bits per symbol is as the Shannon Entropy formula defined: I've read this post, and still not quite understand how is this formula …

Mar 15, 2013 · I just want to point out that there are simple pieces of software around on the Internet claiming to determine (and in fact they do correctly compute according to the formula …

Oct 24, 2018 · I'm trying to understand Shannon's formula for information as entropy in some detail. (I'm obviously not a trained mathematician, so please bear with me). Here's what I …

Jan 2, 2021 · Shannon entropy fundamentally describes how much information per character there is when a stream of the specified probability distribution arrives. Serial correlations and …

Nov 11, 2015 · What are differences and relationship between shannon entropy and fisher information? Why do two kinds of information exist there? Currently, my idea is that it seems …

Jan 29, 2025 · For a binary random variable, entropy is indeed always $\le 1$ (prove this). The point is that you can do better than 1 bit (at least if you aggregate data). E.g., suppose you …

Correct algorithm for Shannon entropy with R Ask Question Asked 11 years, 9 months ago Modified 11 years, 9 months ago

Jul 2, 2024 · The entropy of a quantum state $\rho$ is defined as the Shannon entropy of the probability distribution defined by its eigenvalues. Observe that since a state is a posivitive …