Results 251 to 260 of about 2,925,749 (309)
Some of the next articles are maybe not open access.
1997
Markov chains are central to the understanding of random processes. This is not only because they pervade the applications of random processes, but also because one can calculate explicitly many quantities of interest. This textbook, aimed at advanced undergraduate or MSc students with some background in basic probability theory, focuses on Markov ...
openaire +1 more source
Markov chains are central to the understanding of random processes. This is not only because they pervade the applications of random processes, but also because one can calculate explicitly many quantities of interest. This textbook, aimed at advanced undergraduate or MSc students with some background in basic probability theory, focuses on Markov ...
openaire +1 more source
IEEE Trans. Inf. Theory, 1984
Summary: The Markov chain that has maximum entropy for given first and second moments is determined. The solution provides a discrete analog to the continuous Gauss-Markov process.
Jørn Justesen, Tom Høholdt
openaire +1 more source
Summary: The Markov chain that has maximum entropy for given first and second moments is determined. The solution provides a discrete analog to the continuous Gauss-Markov process.
Jørn Justesen, Tom Høholdt
openaire +1 more source
1992
Abstract In Section 7.3, we briefly introduced models for Markov chains in the simple case where there were only two possible responses: an event occurs or not. However, such models have much wider application. In continuous time models, where each subject is in one of several possible states at any given point, they are often called ...
openaire +1 more source
Abstract In Section 7.3, we briefly introduced models for Markov chains in the simple case where there were only two possible responses: an event occurs or not. However, such models have much wider application. In continuous time models, where each subject is in one of several possible states at any given point, they are often called ...
openaire +1 more source
Reachability problems for Markov chains
Information Processing Letters, 2015We consider the following decision problem: given a finite Markov chain with distinguished source and target states, and given a rational number r, does there exist an integer n such that the probability to reach the target from the source in n steps is ...
S. Akshay +3 more
semanticscholar +1 more source
2006
Motivated by the computational difficulty of analyzing very large Markov chains, we define a notion of clusters in (not necessarily reversible) Markov chains, and explore the possibility of analyzing a cluster “in vitro,” without regard to the remainder of the chain.
Nir Ailon, Steve Chien, Cynthia Dwork
openaire +1 more source
Motivated by the computational difficulty of analyzing very large Markov chains, we define a notion of clusters in (not necessarily reversible) Markov chains, and explore the possibility of analyzing a cluster “in vitro,” without regard to the remainder of the chain.
Nir Ailon, Steve Chien, Cynthia Dwork
openaire +1 more source
Factorization of Markov Chains
Journal of Theoretical Probability, 2004Let \(A\) be a (sub)stochastic \(d\times d\) matrix, with \(d=\infty\) possible. Existence of a factorization \(I-A=(I-B)(I-C)\) is proved for matrices \(B\) and \(C\) which are in particular triangular. The purpose is to solve in two steps equations \((I-A)x=g\) by recurrence. The author's paper [Sb. Math. 189, No.
openaire +2 more sources
The Markov chain of colourings
1995The Markov chain of good (proper) colourings of an n-vertex graph starts with an n-colouring and converges to a uniform distribution over all proper colourings with at most n colours. We study theoretically and experimentally the behaviour of this chain and concentrate in particular on a quantity μ which is the mean number of colours used in the ...
J. Eric Bartels, Dominic Welsh
openaire +1 more source
Theory of Probability & Its Applications, 1961
This paper discusses some new results related to ergodic and limit theorems and also to the repeated logarithm low for inhomogeneous Markov chains. Theorems are formulated and proved for conditions that were not treated in the literature; some estimates obtained previously by S. N. Bernshtein are employed.Lemma 1 is of greatest importance in the paper.
openaire +2 more sources
This paper discusses some new results related to ergodic and limit theorems and also to the repeated logarithm low for inhomogeneous Markov chains. Theorems are formulated and proved for conditions that were not treated in the literature; some estimates obtained previously by S. N. Bernshtein are employed.Lemma 1 is of greatest importance in the paper.
openaire +2 more sources
Markov Chains and Stochastic Stability
Communications and Control Engineering Series, 1993S. Meyn, R. Tweedie
semanticscholar +1 more source