All Questions
Tagged with it.information-theory markov-chains
12 questions
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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}}-\...
- 31
1
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0
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48
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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 ...
- 111
0
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1
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227
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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,...
- 287
2
votes
1
answer
176
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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)=\...
- 59
2
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1
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114
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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)=...
2
votes
1
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185
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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 ...
- 333
2
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1
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290
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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 ...
- 6,853
1
vote
0
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83
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Convexity of conditional relative entropy for Markov distributions
Consider two Markov processes $p$ and $q$. The conditional relative entropy between them is
\begin{align}
D(p\parallel q)& =\sum_a p(a)\sum_b p(b\mid a)\log\frac{p(b\mid a)}{q(b\mid a)}\\
& =\...
- 11
0
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1
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207
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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 ...
- 1,109
3
votes
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494
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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 ...
- 1,109
2
votes
0
answers
162
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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 ...
- 1,109
9
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2
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3k
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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 ...
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