Conditional steady-state bounds for a subset of states in Markov chains
SMCtools'06: Proceeding from the 2006 Workshop on Tools for Solving Structured Markov Chains
Please cite this item using this persistent URLhttp://hdl.handle.net/11693/27135
The problem of computing bounds on the conditional steady-state probability vector of a subset of states in finite, ergodic discrete-time Markov chains (DTMCs) is considered. An improved algorithm utilizing the strong stochastic (st-)order is given. On standard benchmarks from the literature and other examples, it is shown that the proposed algorithm performs better than the existing one in the strong stochastic sense. Furthermore, in certain cases the conditional steady-state probability vector of the subset under consideration can be obtained exactly. Copyright 2006 ACM.
- Conference Paper 
Showing items related by title, author, creator and subject.
Simon F.; Guillen P.; Sagaut P.; Lucor, D. (2010)The present paper focus on the stochastic response of a two-dimensional transonic airfoil to parametric uncertainties. Both the freestream Mach number and the angle of attack are considered as random parameters and the ...
Kabanov, Y.; Pergamenshchikov, S. (1997)A limit of attainability sets is found for a linear two-scale stochastic system for the case when the diffusion coefficient of the fast variable is of order ε1/2. The attainability set is defined as the set of distributions ...
Goken, C.; Gezici, S.; Arikan, O. (2010)In this paper, stochastic signaling is studied for scalar valued binary communications systems over additive noise channels in the presence of an average power constraint. For a given decision rule at the receiver, the ...