# Tagged Questions

This tag is for [Entropy](http://en.wikipedia.org/wiki/Entropy_(information_theory)) in Mathematics.

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### Entropy of Sum vs Difference of Random Variable

I am looking for a proof of the following fact Let X and X' be i.i.d on {0,1,2}(not necessarily uniform). Prove that $H(X + X' mod\;3) \leq H(X - X' mod\;3)$ where $H()$ is the standard Shannon ...
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### If $g$ is a function of the random variable $X$, is it true that $H(X) = H(X) + H(g(X)\mid X)$?

I think my homework about entropy is formulated incorrectly. The question is the following: let $X$ be a discrete random variable. Show that the entropy of a function $g$ of $X$ is less than or ...
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### Calculate $\lim_{n\rightarrow \infty}\frac{\log{\binom{n}{n_1}}}{n}$

We know that $\lim_{n\rightarrow \infty}\frac{n_1}{n}=p$ and $0\leq p\leq 1$. Based on this information I want to calculate $\lim_{n\rightarrow \infty}\frac{\log{\binom{n}{n_1}}}{n}$. Any help? Note: ...
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### Entropy of convolution of measures

Let $G$ be a countable, discrete group, and let $\mu_1,\mu_2$ be probability measures on the group $G$. We define the entropy of $\mu_i$ as $H(\mu_i)=\sum\limits_{g \in G}-\mu_i(g)\log(\mu_i(g))$ ...
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### Renyi entropy (zeroth order)

I am reading a book on information theory, therein has been introduced Renyi entropy of order $\alpha$ as $S_{\alpha} = \frac{1}{1-\alpha}\log(Tr\rho^{\alpha})$, where $\rho$ is density matrix. It ...
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### Relative Entropy and variation formula for $C_c$

Let $R(\mu \mid \nu ) = \int_{\mathbb R} \log \frac{d\mu}{d\nu} d\nu$ for $\mu, \nu$ probability measures over $\mathbb R$. By the varational representation formula of Donsker and Varadhan we know ...
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### Statistical Inference, Differential Geometry and Entropy

Context: Statistical Inference and Differential Geometry Let's consider a generic $p(x;\theta)$ distribution with $\theta$ Parameters Vector, it is obvious that $$\int p(x; \theta) dx = 1$$ ...
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### Conditional Entropy in rolling a dice

A 6-sided die is tossed once. Two events X and Y are defined. X is the event in which an even number comes up and Y is the event in which the number is a multiple of 3. The value of H(X|Y) needs to be ...
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### Channel Capacity of a Cycle Graph

I have the following problem: Given a discrete memoryless channel $Y = X + Z \mod5$, where $X$ is selected from one of 5 symbols (0, 1, 2, 3, 4), $Z$ randomly selected from (-1, 0, 1), and $X$ and $Z$ ...
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### prove a theorem about an upper bound of entropy of a random vector

There is a theorem that: if Z is any zero-mean, complex random vector with covariance $E[ZZ^H]=R_z$, then $H(Z)\leq \log|{\pi eR_z}|$, with equality holding if and only if Z has a circularly ...
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### Entropy of bit position in a bit stream

8 bit strings are sent over a channel. First two bits are always 1. Last six bits can be either 0 or 1. Receiver randomly selects bit-position and reveals bit but not its position. If X is the random ...
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### How to compute the topological entropy of a permutation?

I have a permutation, say as ${4,1,7,2,3,5,6}$, given by its induced matrix. According to this paper (Proposition 11 on p. 82), To compute its topological entropy, one can compute the ...
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### Relationship between compression, shannon entropy and kolmogorov complexity

I have read that the Shannon Entropy is used as a bound for the compressibility of a message, for example here 1 it says "In other words, the best possible lossless compression rate is the entropy ...
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### prove this inequality related to probability and information theory

How do I prove this? I'm thinking I should use Jensen's inequality somehow. $$\sum_K p_k(1-p_k) \le -\sum_K p_k\log p_k$$ The assumption that $\sum_K p_k=1$ holds.
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### Normalization of data in decision tree

After reading through a few references, I have come to know that for machine learning in general, it is necessary to normalize features so that no features are arbitrarily large ($centering$) and all ...
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### Tools to compress a finite list as a function

Can someone show me some tool to a lossless compression in an algorithm of a finite list of rational numbers? By example this list A=(0,1,3,2,-1,-2,0), there is a way to construct an algorithm or ...
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### What is the correct equation for conditional relative entropy and why

I was trying to understand the concept of conditional relative entropy. As in: $$D(P(X\mid Y) ||Q(X\mid Y))= E [\log\frac{P(X\mid Y)}{Q(X\mid Y)}]$$ I would have thought that its equations would ...
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### Counting graph isomorphisms and entropy

Question: If all graphs on $n$ vertices are given equal probability, what does the induced probability distribution on the graph isomorphism classes look like? Are there any patterns that emerge as ...
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### Entropy derivation from Multiplicity

Multiplicity(W)= N!/(n1!*n2!....ni!) Entropy = 1/N * ln W = 1/N*ln N! - 1/N*sigma_for_all_i(ln ni!) As N->infinity, By Stirlings approximation ...
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### Meaning of this term:$H(X \oplus\hat{X}|\hat{X} )$

Here, $H$ means the entropy function. I understand that the symbol $\oplus$ means modulo $2$ addition. But I don't understand the significance of the entire expression.
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### What connections between computer science and ergodic theory?

I have a background in ergodic theory, but I am switching to computer science/programming. I would like to know if tools from ergodic theory could be useful, especially something around coding of ...
Having $X$ and $Y$ discrete random variables above finite set. Z is defined as $Z=X+Y$ when does the following happen: $$H(Z)=H(X)+H(Y)$$
For a hyperbolic PDE of the form $$u_t + f(u)_x = 0$$ it turns out that the right notion of solution is entropy solution. Now, the notion of classical solutions are obviously very natural, and also ...