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

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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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111 views

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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30 views

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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37 views

Relation between entropy and compressibility of a file

Suppose I have an ordered list of bytes (the hexdump of some object file), and wish to calculate the information entropy of this file. My understanding is I can calculate this as $$ \sum_{n=0}^{n=255} ...
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198 views

Upper bound on the entropy of a sum two random variables

Let $X$ be a random variable such that $|X| \leq A$ almost surely, for some $A > 0$. Let $Z$ be independent of $X$ such that $Z \sim {\cal N}(0, N)$. My question is: How large can the entropy ...
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116 views

Measuring the entropy of a graph representing a transition probability matrix of a first order markov chain

There's a research project i'm currently working on which requires me to analyze various aspects of "worlds" represented by transition probability matrices, where the nodes represent objects in the ...
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29 views

Finite shannon entropy and mutual information

I was wondering, if it can be shown that the shannon entropy for continuous random variables are finite, such that $H(X)=-\int_{-\infty}^{\infty}f(x)*log(f(x)) dx < \infty$ and the same question ...
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1answer
246 views

Entropy of the product of two random variables

Consider a random matrix $X$ and a random vector $Y$. Let the Shannon entropies $H(X) = H(Y) = n$. Is there a simple upper bound for entropy $H(XY)$? I believe $H(XY) \leq 2n$ as that is a simple ...
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63 views

partition with infinite entropy?

Let $P$ be an infinite partition of the interval $[0,1]$. Let $P$ have elements $I_i$ which has Lebesgue measure $m(I_i)$. Then the entropy of $P$ is defined by $\sum_i -m(I_i)\log m(I_i)$. Can this ...
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21 views

Mutual information staying constant under composition of channels

Consider the following scenario: one has 2 communication channels $C_1$ and $C_2$. Let $p_0(x)$ be some arbitrary but fixed input probability distribution. The mutual information between the input ...
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1answer
34 views

how to find the maximum of the cross-entropy of a discrete random variable?

For a discrete random variable $x$, the cross entropy is $$H(x) = -(p_1\log p_1+\cdots+p_n\log p_n)$$ , so what is the maximum of $H(x)$? Here is what I tried, I compute the gradient as follows ...
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Entropy of matrix vector product

Consider a random $n$ by $n$ circulant matrix $M$ whose entries are chosen independently and uniformly from $\{0,1\}$. Let $M'$ be the $m$ by $n$ matrix which is formed by taking the first $m$ rows of ...
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1answer
62 views

If a series converges, does it converge with additional log term multiplied?

If $\sum_{n} |a_n| < \infty$, is it true that $\sum_{n} |a_n\log(a_n)| < \infty$ if $0 \leq a_n \leq 1$? I am trying to see if $A$ is trace class operator, then $A \log(A)$ is also trace class ...
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1answer
15 views

InformationGain on Two Continuos classes instead on inary

I've a problem regarding an excersise with information gain. I can't seem to get the right answer, because the excersises differs from what we learned. Usually, a target class is a binary variable ...
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1answer
42 views

Trying to understand the math in a neuroscience article by Karl Friston

I am trying to understand a neuroscience article by Karl Friston. In it he gives three equations that are, as I understand him, equivalent or inter-convertertable and refer to both physical and ...
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203 views

Finding a specific sequence of digits in pi

Looking at the pifs project on GitHub and this question on SO has made me curious as to how feasible it is to find a specific sequence of digits within Pi. Essentially, on average, how many digits of ...
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208 views

calculate channel capacity and maximum conditional entropy

i want to know when it is equal channel capacity or $I(X,Y)$ maximum or where $I(X,Y)=H(X)-H(X\mid Y)=H(Y)-H(Y\mid X)$ now if we have two random variable with some specific distribution ...
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35 views

when it is conditional entropy minimized?

for example let us consider following table know that entropy of variable is maximum when it is equally distributed,all of it's variable has equal probability,but what about joint entropy or ...
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94 views

conditional entropy calculation

let us consider following table i am asked to calculate conditional entropy,from table i have understood everything,for instance how to calculate marginal probabilities,also i know formula for ...
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1answer
37 views

What's the sum of all events? (not the sum of all probabilites of events)

I need to calculate the entropy $h(X|Y)$, where $Y=X^2$. In this case, I suppose $\mathrm p(x|y)=\frac{1}{2}$. For the entropy \begin{align} h(X|Y) &= \int\limits_y \mathrm p(y)\ h(X|Y=y)\ ...
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39 views

continuous, non-additive set function

I am looking for a non-additive, continuous set function from a simplex $\Pi_{n}$ of finite dimension $n-1$ into $[0,\infty]$. The motivation is as follows. Shannon defined the entropy ...
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67 views

Compressing binary numbers

If I have a arbitrarily long random binary number with the condition that the probability that a given digit is 0 and 1 is 1/4 and 3/4, respectively. What is the best way to compress this into a ...
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1answer
158 views

How is the formula of Shannon Entropy derived?

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 ...
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Few questions regarding applications of conditional entopy

I have the idea of entropy and conditional probability etc and having few conditional entropy related questions: 1. What does actually conditional entropy $H(Y|X)$ mean? How can we explain this term ...
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32 views

Mutual information decrease with coarse-graining

Let $X,A,Y,B,C,D$ be random binary variables. $D$ is independent from $X,A,C$ and $C$ is independent from $Y,B,D$. Is it true that: If $I(Y:B|D=0)\leq \epsilon$ then $I(X\oplus Y:A\oplus ...
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28 views

Gaussian distribution variance estimation

It's well known if I have a process generating normally distribuited data, I can estimate the parameters of the gaussian function: ...
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59 views

Prove that bitstrings with 1/0-ratio different from 50/50 are compressable

I'm looking for a proof, that $$ \sum_{i=0}^{\lambda n} \binom{n}{i} \le 2^{nH(\lambda)} $$ with $n>0$, $0 \le \lambda \le 1/2$ and $ H(\lambda)=-[\lambda log \lambda + (1-\lambda) log (1-\lambda)] ...
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172 views

Entropy of the induced transformation

I need help with this problem: Let $(X,\mathcal{B},\mu,T)$ be a ergodic dynamical system in the probability space $(X,\mathcal{B},\mu)$. Let $A \in \mathcal{B}$ with $\mu(A)>0$. We define the ...
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73 views

Variational Methods, why KL divergence is the difference between true distribution and approximating distribution.

Likelihood = $L(\textbf{w}) = P(V\mid \textbf{w})$. $$\ln P(V\mid \textbf{w}) = \ln \sum_H P(H,V\mid \textbf{w})$$ $$= \ln \sum_H Q(H\mid V)\frac{P(H,V\mid \textbf{w})}{Q(H\mid V)}$$ $$\geq ...
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60 views

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 ...
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74 views

Entropy of sum is sum of entropies

Having $X$ and $Y$ discrete random variables above finite set. Z is defined as $Z=X+Y$ when does the following happen: $$H(Z)=H(X)+H(Y)$$
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intuition for entropy solutions

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 ...
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Entropy of sum of two Uniform random variables

say $X$ and $Y$ are two identical, independent and discrete Uniform random variables and $Z=X+Y$. I do not know more about the random variables. Assuming $H(\cdot)$ to be the entropy of a random ...
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45 views

Prove identity involving the Tsallis q-logarithm

The natural logarithm and the exponential can both be generalized to a called q-logarithms and q-exponentials.those functions are defined as follows: \begin{eqnarray} \log_q(x) &:=& ...
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What is the “true” entropy of a binary string?

Consider an infinite binary string $\sigma$ and define its entropy $$H_1 = -(p_0 \log_2 p_0 + p_1 \log_2 p_1)$$ with $p_i = \lim_{N\rightarrow \infty} N(i)/N$, $N(i)$ the number of $i$'s among the ...
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Problem with calculating probability of symbols

I've a $100 \times 100$ binary matrix it`s constructed with this probability table : i want to apply extended Huffman on this matrix my idea is to compress each column individually . - so starting ...
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23 views

Can we calculate entropy for nonstationary random variables?

Let's assume that $X$ is a discrete random variable, which can take any value from the set $\{x_0,\dots,x_n\}$ with the probability mass function $P(X)$. We can calculate the entropy of $X$ as ...
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34 views

Continuity of Shannon Entropy with respect to KL-Divergence distance

I am trying to prove the following statement which seems to be trivial but I cannot: Suppose $p$ and $q$ are two distributions. If $D(p||q) < \epsilon$ and $D(q||p) < \epsilon$ for some ...
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Generlized Entropy compared to Generalized Dimension

I am currently reading the following paper by F.Takens: Multifractal analysis of dimensions and entropies. This paper discusses two different measures. One is generalized entropies and the other is ...
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58 views

necessity of uniform continuity for topological entropy

I am referring to Walters' book "Introduction to Ergodic Theory." When he defines the concept of topological entropy he always assumes that the transformation $T: X \rightarrow X$ is uniformly ...
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15 views

Comparing a vector with a sorted vector

I am currently looking at a database in which the tuples have a natural order in which each tuple has an integer ID that reflects its age. The more recent the tuple, the larger its ID. Now we are ...
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78 views

Huffman codes: does less entropy imply less weighted average codeword length?

Let $\Sigma$ be a source alphabet with a probability distribution over its symbols $P$. Then, the Shannon entropy of $\Sigma$ is $$-\sum p_j \times -\mbox{log}_2(p_j)$$ where $p_j$ is the probability ...
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1answer
50 views

Subadditivity of Entropy

We define $H(X) = -\sum_{x}p_{x}\log p_{x}$ and relative entropy as $H(p(x)||q(x)) = \sum_{x}p(x)\log \frac{p(x)}{q(x)} = -H(X)-\sum_{x}p(x)\log q(x).$ Now we have to prove that $H(X,Y,X) + H(Y) \leq ...
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Understanding conditional entropy intuitively $H[Y|X=x]$ vs $H[Y|X]$

I was trying to understand conditional entropy better. The part that was confusing me exactly was the difference between $H[Y|X=x]$ vs $H[Y|X]$. $E[Y|X=x]$ makes some sense to me intuitively because ...
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how can prove this statement?

According definition of Kullback–Leibler divergence, we have: $"k[f|g]=\int_{}^{} f(x)\log \frac{f(x)}{g(x)}\mathrm dx"$. Now How can I prove this statement:$$k[f|g]=k[f|w]k[w|g].$$ Thanks in advance. ...
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Are measures of information model specific?

Does an information measure for a signal do a better job if it assumes some things about the signal? For example: I have a digital stream of data, 0s and 1s coming at a clock rate $r$. What is the ...
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Solomonoff induction , Shannon Entropy, Kolmogorov Complexity.

If Expected Kolmogorov Complexity equals Shannon Entropy why can't Shannon Entropy be used as an approximation of Kolmogorov Complexity in Solomonoff Induction? Regarding Kolmogorov Complexity and ...
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61 views

toplogical entropy of general tent map

Measure theoretic entropy of General Tent maps The linked question made me wonder how to calculate the topological entropy of a general tent map. Let $I=[0,1]$ and $\alpha \in ( 0,1)$. Define $T: I ...
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136 views

Fano's inequality and error rate

The Wire-tap channel II (http://link.springer.com/chapter/10.1007%2F3-540-39757-4_5) article in proof of Theorem 1 uses Fano's inequality to estimate the entropy $H(S|\hat{S}) \leq K \cdot h(P_e)$ ...
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Looking for a a measure-theoretic treatment of “differential entropy”

If $X$ is a discrete random variable, its entropy $H(X)$ is usually defined as something along the lines of $-\sum \def\P{\mathbb{P}}\P(x) \log_2( \P(x))$, where the sum ranges over all the possible ...