Wireless channels usually face bursty errors, i.e., errors are prone to occur in clusters. These bit errors can be modeled using the Gilbert-Elliott model. When data packets are t...
We demonstrate how to apply Coupling from the Past, a simulation technique for exact sampling, to Markov chains based on TCP variants. This approach provides a new, statistically ...
We consider the problem of sampling almost uniformly from the set of contingency tables with given row and column sums, when the number of rows is a constant. Cryan and Dyer [3] h...
Mary Cryan, Martin E. Dyer, Leslie Ann Goldberg, M...
Abstract. In this paper, we propose a Markov chain for sampling a random vector distributed according to a discretized Dirichlet distribution. We show that our Markov chain is rapi...
We analyse the convergence of a GA when the mutation probability is low and the selection pressure is high, for arbitrary crossover types and probabilities. We succeed in mathemat...
The paper presents an extension of Vose’s Markov chain model for genetic algorithm (GA). The model contains not only standard genetic operators such as mutation and crossover bu...
We propose in this paper a novel approach to the induction of the structure of Hidden Markov Models. The induced model is seen as a lumped process of a Markov chain. It is construc...
Stochastic bounds are a promising method to analyze QoS requirements. Indeed it is sufficient to prove that a bound of the real performance satisfies the guarantee. However, the...
The analysis of discrete stochastic models such as generally distributed stochastic Petri nets can be done using state space-based methods. The behavior of the model is described ...
A steganalysis system based on 2-D Markov chain of thresholded prediction-error image is proposed in this paper. Image pixels are predicted with their neighboring pixels, and the ...