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

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22
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An information theory inequality which relates to Shannon Entropy

For $a_1,...,a_n,b_1,...,b_n>0,\quad$ define $a:=\sum a_i,\ b:=\sum b_i,\ s:=\sum \sqrt{a_ib_i}$. Is the following inequality true?: $${\frac{\Bigl(\prod a_i^{a_i}\Bigr)^\frac1a}a \cdot ...
10
votes
3answers
3k views

Is there a “most random” state in Rubik's cube?

Is there a state in Rubik's cube which can be considered to have the highest degree of randomness (maximum entropy?) asssuming that the solved Rubik's cube has the lowest?
9
votes
1answer
3k views

Entropy of a binomial distribution

How do we get the functional form for the entropy of a binomial distribution? Do we use Stirling's approximation? According to Wikipedia, the entropy is $\frac1 2 \log_2 \big( 2\pi e\, np(1-p) \big) + ...
9
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3answers
380 views

Does $\operatorname{div}\left(\nabla G +xG\right)=0\Longleftrightarrow \nabla G +xG=0$?

Let $G$ be a smooth function defined on $\textbf{R}^d$. What are the assumptions I should use to assume that $$\operatorname{div}\left(\nabla G(x) +xG(x)\right)=0 \quad (\forall x\in \textbf{R}^d)$$ ...
8
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2answers
526 views

Can the entropy of a random variable with countably many outcomes be infinite?

Consider a random variable $X$ taking values over $\mathbb{N}$. Let $\mathbb{P}(X = i) = p_i$ for $i \in \mathbb{N}$. The entropy of $X$ is defined by $$H(X) = \sum_i -p_i \log p_i.$$ Is it possible ...
7
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1answer
209 views

Lemma in Petersen's *Ergodic Theory*

I'm trying to understand the proof of Lemma 6.2.1 (p.260-261) in Petersen's Ergodic Theory. Specifically, I don't understand why $B_{n}^{A} \in \mathscr{B}(T^{-1}\alpha \vee \dots \vee T^{-n}\alpha)$ ...
7
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1answer
73 views

Structure of equientropic transformations

Given a probability vector $v=(v_1,\ldots,v_n)$ with $1\geq v_i\geq 0$ and $\sum_{i=1}^n v_i=1$ its entropy can be defined as: $$ H(v):=-\sum_{i=1}^nv_i\log v_i $$ I wonder what is known about ...
7
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0answers
129 views

Approximation of Shannon entropy by trigonometric functions

Define Shannon entropy by $$I(p) = -p \log_2 p$$ Numerical experimentation shows that $\sin(\pi p)^{1-1/e}$ is a good approximation to $I(p) + I(1-p)$ on $[0,1],$ never differing by more than 3.3%. ...
6
votes
3answers
610 views

What is information theoretic entropy and its physical significance?

I have learned entropy in my information theory classes. The definition I got from text books was the average information content in a message sequence etc. But in one of the MIT videos related to ...
6
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2answers
2k views

How Entropy scales with sample size

For a discrete probability distribution, the entropy is defined as: $$H(p) = \sum_i p(x_i) \log(p(x_i))$$ I'm trying to use the entropy as a measure of how "flat / noisy" vs. "peaked" a distribution ...
6
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1answer
291 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 ...
6
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1answer
157 views

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 ...
5
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3answers
1k views

Inverse of binary entropy function for $0 \le x \le \frac{1}{2}$

I'm trying to find the inverse of $H_2(x) = -x \log_2 x - (1-x) \log_2 (1-x)$[1] subject to $0 \le x \le \frac{1}{2}$. This is for a computation, so an approximation is good enough. My approach was ...
5
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2answers
3k views

Entropy of matrix

I am trying to understand entropy. From what I know we can get the entropy of a variable lets say X. What i dont understand is how to calculate the entropy of a matrix say m*n. I thought if columns ...
5
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1answer
356 views

Pinsker $\sigma$ Algebra

Let $(X,A,\nu)$ be a probability space and $T:X\to X$ a measure-preserving transformation. The Pinsker sigma algebra is defined as the lower sigma algebra that contains all partition P of measurable ...
5
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1answer
72 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)] ...
5
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1answer
177 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 ...
5
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2answers
1k views

Can I normalize KL-divergence to be $\leq 1$?

The Kullback-Leibler divergence has a strong relationship with mutual information, and mutual information has a number of normalized variants. Is there some similar, entropy-like value that I can use ...
5
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0answers
85 views

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 ...
5
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0answers
76 views

Decrease of entropy when iterating a random discrete function

Let $m$ be a positive integer. Let $S$ be the set of non-negative integers $x$ less than $m$, with $|S|=m$. Let $X_0$ be the discrete uniform distribution over $S$, with $P(x)=\begin{cases} 1/m & ...
5
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1answer
237 views

A tight lower bound for the entropy of the XOR of two random variables

Let $U$ be the uniform random variable over $n$-bit binary strings, and let $X$ be another random variable that is dependent on $U$ and ranges over $n$-bit binary strings. Assuming $I(X;U) \le ...
4
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3answers
219 views

Probability and Entropy

According to the Wikipedia article on conditional entropy, $\sum p(x,y)\log p(x)=\sum p(x)\log p(x)$. Can someone please explain how?
4
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2answers
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Derivation of the maximum entropy distribution

I am reading a book and having trouble following something. The problem is to try to maximize the differential entropy $-\int_{0}^{\infty}p(r)\log p(r)$ under the constraints that ...
4
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2answers
92 views

Are there logarithm functions for arbitrary rings?

The logarithm function for $\mathbb{R}$ satisfies $\log xy = \log x + \log y$ whenever both $\log x$ and $\log y$ are defined. Are their conditions for a ring $R$ which guarantee the existence of a ...
4
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1answer
260 views

Definition of the Entropy

I have a question regarding definition of entropy by expected value of the random variable $\log \frac{1}{p(X)}$: $H(X) = E \log \frac{1}{p(X)}$, where $X$ is drawn accordingly to the probability ...
4
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1answer
412 views

Does a maximum entropy probability distribution with KL-divergence constraint not exist?

In my earlier question I asked about a technical aspect of solving a system of equations arising from looking for an entropy-maximizing distribution $p(x)$ continuous on $\mathbb{R}$ and constrained ...
4
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1answer
149 views

Definition of entropy of an ergodic measure

I'm reading a paper in which it is stated that The entropy of an ergodic measure is defined as $$\lim_{n \to \infty} -\frac{1}{n} \sum_{|w|=n} \mu[w] \log \mu[w].\tag{1} \label{eq:1}$$ Here ...
4
votes
1answer
248 views

Non-zero Conditional Differential Entropy between a random variable and a function of it

Let two continuous random variables, where the one is a function of the other: $X\, $ and $\, Y=g\left(X\right)$. Their mutual information is defined as ...
4
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1answer
62 views

Inequality on Shannon's entropy

Let $P$ be a set of probabilities s.t. $\sum_{p_i \in P} p_i = 1$. Moreover, let $H(P)$ the Shannon's entropy of the set of probabilities $P$: $$ H(P) = -\sum_{p_i \in P} p_i \log_2 p_i $$ I define ...
4
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0answers
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A combinatorial problem.

Let be $(X, \mathbb{A}, \mu)$ a measure space, a partition of $ X $ is a disjoint family $\xi=\{P_1,\ldots,P_k \}$ of measurable sets such tath $\bigcup P_i=X\pmod0).$ If $\xi=\{P_1,\ldots,P_k ...
4
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1answer
415 views

Notation of cross entropy

I have a question regarding a notation that seems to be very usual. For starters, cross entropy is defined by: \begin{align}H(X, q) &= H(X) + D(p||q) \\ & =-\sum_x p(x)\log_2 q(x)\end{align} ...
3
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3answers
280 views

Estimating the entropy

Given a discrete random variable $X$, I would like to estimate the entropy of $Y=f(X)$ by sampling. I can sample uniformly from $X$. The samples are just random vectors of length $n$ where the entries ...
3
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3answers
915 views

Is Standard Deviation the same as Entropy?

We know that standard deviation (SD) represents the level of dispersion of a distribution. Thus a distribution with only one value (e.g., 1,1,1,1) has SD equals to zero. Similarly, such a distribution ...
3
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1answer
265 views

Entropy of geometric random variable with parameter $1/2$

I'm studing for an information theory exam, maybe some of you can help me here with an exercise. What's the entropy of $X$ as $\{1,2,\ldots,n\}$ ($n$=infinity) where the probabilities are $P ...
3
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3answers
486 views

Relationship between entropy and ergodicity

Are there any direct connections between entropy and ergodicity? For example, does knowing that $(X,\mathcal{S},\mu,T)$ is ergodic help in computing the entropy? I know that there are some indirect ...
3
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3answers
155 views

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 $H(\mu_i)=\sum\limits_{g \in G}-\mu_i(g)\log(\mu_i(g))$ ...
3
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2answers
81 views

Proof of recursivity of Shannon's Entropy

Does anybody know a book where the proof of recursivity property of Shannon's Entropy can be found? I mean this: $$H(q_1,...,q_n)=H(q_1 + q_2, q_3,...,q_n) + (q_1 +q_2)H( \frac{q_1}{q_1+q_2} , ...
3
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1answer
53 views

Do the pth powers of $p$-norms define the same partial ordering on the set of all probability distributions for all $p>1$?

Consider the $p$-th power of the Schatten $p$-norm $||q||_p$ of a probability distribution $q$ , ie, the function $\sum_j q_j^p$, where $\sum_j q_j = 1$ and $q_j \geq 0$. For fixed $q$ and $p>1$ ...
3
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2answers
89 views

What is the CONCEPT when we speak of maximum entropy?

What is an intuitive interpretation of the concept of maximum entropy? I want to understand this concept better but what I'm finding is too "advanced" right now. Can anyone simplify it ... imagine I'm ...
3
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1answer
45 views

Definition of topological entropy

What the meaning of the limit that appears in the definition of topological entropy? Let $X$ a compact metric space and $f\colon X\to X$ a continuous function and a subset $K \subset X$. The ...
3
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1answer
69 views

“Empirical” entropy.

Information entropy is usually defined as $$\text{I}_b({\bf p}) = -\sum_{\forall i}p_i\log_b(p_i)$$ i.e. the expected value of the negative logarithm of the probabilities. This is all good when we ...
3
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1answer
52 views

Fano's Inequality Proof

For an information theory class, I am studying the proof for Fano's inequality, i.e.: $H(P_e) + P_elog(|X|) \geq H(X|\hat{X}) \geq H(X|Y)$ Where $H(X)$ is the entropy of the random variable X ...
3
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1answer
80 views

Topological Entropy of $(x,y)\mapsto(x+y,x+a)$

Let $a\in \mathbb T^1$, how can I calculate the topological entropies of the maps $T_1:(x,y)\mapsto(x+y,x+a)$ and $T_2 : (x,y) \mapsto (x+y,y+a)$ defined on $\mathbb T^2$. Here $\mathbb T^n$ is the ...
3
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1answer
62 views

How to consider gravity as an entropic force?

Is it possible to consider gravity as an entropic force? What is mathematical relation between second law of thermodynamics and newton law of gravity?
3
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1answer
533 views

Maximum entropy joint distribution from marginals?

How does one find the maximum entropy joint distribution of two random variables X and Y given their marginal probability mass functions? I know: I have the marginals, meaning p(x) and p(y) are ...
3
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1answer
99 views

Shannon's entropy in a set of probabilities

Let $P = p_1, \ldots, p_N$ be a set of probabilities (i.e., $0 \leq p_i \leq 1$). I can compute the Shannon's entropy as follows: $$ H(P) = -\sum_{i=1}^N p_i \log_2 p_i $$ Now, suppose I perform the ...
3
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1answer
127 views

convergence of entropy and sigma-fields

This question is related to this one. Let $(X_1, X_2, \ldots)$ be a sequence of random variables such that each $X_n$ takes its values in a finite space, say $\{0,1\}$, and the $\sigma$-field ...
3
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2answers
131 views

Calculate entropy with n values

I trying to solve a quiz that asks the following. The variable $X$ can be the values $1,2,3,...,n$ with the probabilities $\frac{1}{2^1}, \frac{1}{2^2},\frac{1}{2^3},...,\frac{1}{2^n}$ How can I ...
3
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1answer
177 views

Intuition about the relation of combinations and entropy

It is not difficult to show that $${n \choose \lambda n} \leq 2^{H(\lambda)n}$$ where $H$ is the binary entropy function: $$H(\alpha) = -\alpha \lg \alpha - (1-\alpha)\lg (1-\alpha)$$ I was ...
3
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1answer
89 views

Is $H(X)<E(X)$ for natural $X$?

For an RV $X$ with values on $\{1,2,\ldots\}$, I need to prove that the entropy is less than the EV: $H(X)\leq E(X)$ . I tried to bound the log but I'm not quite there. Appreciate any hint... Thanks