Skip to main content

All Questions

Filter by
Sorted by
Tagged with
9 votes
2 answers
3k views

Is this a situation where triple mutual information is always non-negative?

Suppose I have three identically-distributed homogeneous continuous-time discrete state space Markov chains $X_1(t), X_2(t), X_3(t)$, $t\geq 0$. They evolve independently but share a common random ...
Paul Tupper's user avatar
3 votes
0 answers
494 views

Maximization of a total variation distance subject to another total variation distance in Markov chain

Suppose two dependent random variables $X$ and $V$ from finite alphabets $\mathcal{V}$ and $\mathcal{X}$ with known joint and marginal distributions are given. Let $P_{XV}$ and $P_X$ and $P_V$ are the ...
math-Student's user avatar
  • 1,109
2 votes
1 answer
185 views

Entropy rate problem of ergodic Markov process with non-ergodic joint

I have a problem with the entropy rate when two ergodic Markov processes who are independent of each other having a non-ergodic joint. More specifically let us consider two finite-state Markov ...
Yi Huang's user avatar
  • 333
2 votes
1 answer
176 views

Monotonicity of Dirichlet form of Markov chain

Consider a continuous-time, irreducible Markov chain $X_t$ on a finite state space $E$. Assume the jump rates are $R(x,y)$ for $x,y\in E$, the generator is $L$, i.e for any function $f$ on E, $$Lf(x)=\...
Tiago's user avatar
  • 59
2 votes
1 answer
114 views

Strong Data Processing Inequality for capped channels

Let $X$ and $Y$ be two $\rho$ correlated Gaussian vectors, such that $X,Y\sim N(0,1)^n$ and $E[X_iY_i]=\rho$. Let $M_X = f(X)$ and $M_Y = f(Y)$ be $k$-bit functions of $X$ and $Y$, that is $H(X)=H(Y)=...
Thomas Dybdahl Ahle's user avatar
2 votes
1 answer
290 views

Uniform upper bound on contraction coefficient w.r.t total-variation metric, of a certain set of block-diagonal Markov kernels

Disclaimer. This is related to another question I've asked on the TCS site https://cstheory.stackexchange.com/q/46097/44644. I'm new to information theory (and other relevant fields). It's even ...
dohmatob's user avatar
  • 6,853
2 votes
0 answers
162 views

An optimization in Markov Chain

We are given two correlated random variables $V$ and $X$ supported over a finite alphabets $\mathcal{V}$ and $\mathcal{X}$. Suppose the marginal $P_V$ and conditional distribution $P_{X|V}$ are ...
math-Student's user avatar
  • 1,109
1 vote
0 answers
48 views

Sample complexity of estimating a doubly stochastic matrix

Let $P\in\mathbb{R}^{n\times n}$ be a doubly-stochastic matrix. That is: $$P(x,y)\geq 0,\quad \sum_xP(x,y)=1,\quad \sum_yP(x,y)=1.$$ I would like to know if lower and upper bounds on the sample ...
user134977's user avatar
0 votes
1 answer
207 views

On the inverse problem of Dobrushin

Dobrushin, in this paper, looked into the following problem. Suppose We are given a Markov kernel (conditional distribution) $P_{Y|X}$. Information theorist usually call $W$ a channel. It is known ...
math-Student's user avatar
  • 1,109
0 votes
0 answers
34 views

Does the definition of mixing time work for general non-Markovian processes?

A definition of the mixing time for Markov chains is given by \begin{equation} \tau_{\text{mix}}\equiv\inf{\{t>0: \sup_i\left\vert \frac{\boldsymbol{p}(t|p_j(0)=\delta_{ij})}{\boldsymbol{\pi}}-\...
Richard Ben's user avatar
0 votes
1 answer
227 views

Constructing Markov chain

Let $(A_1,B_1)$ and $(A_2,B_2)$ be two random variables with the joint distributions $p_{A_1B_1}$ and $p_{A_2B_2}$, respectively. Moreover, we have $$\mathbb{P}[(A_1,B_1)\neq (A_2,B_2)]=\alpha.$$ Then,...
Math_Y's user avatar
  • 287