We investigate almost uniform sampling from the set of linear extensions of a given partial order. The most efficient schemes stem from Markov chains whose mixing time bounds are polynomial, yet impractically large. We show that, on instances one encounters in practice, the actual mixing times can be much smaller than the worst-case bounds, and particularly so for a novel Markov chain we put fo...

Markov chain models are commonly used for content-based appraisal of coding potential in genomic DNA. The ability of these models to distinguish coding from non-coding sequences depends on the method of parameter estimation, the validity of the estimated parameters for the species of interest, and the extent to which oligomer usage characterizes coding potential. We assessed performances of Mar...

A class of multiscale stochastic models based on scale-recursive dynamics on trees has recently been introduced. Theoretical and experimental results have shown that these models provide an extremely rich framework for representing both processes which are intrinsically multiscale, e.g., 1=f processes, as well as 1-D Markov processes and 2-D Markov random elds. Moreover, eecient optimal estimat...

A class of multiscale stochastic models based on scale-recursive dynamics on trees has previously been introduced. Theoretical and experimental results have shown that these models provide an extremely rich framework for representing both processes which are intrinsically multiscale, e.g., 1/f processes, as well as 1D Markov processes and 2D Markov random fields. Moreover, efficient optimal est...

This paper concerns on modeling of traffic flow as a hybrid approach that combines continuous and discrete dynamics in a system. The model is chosen as simple as possible such as a Hidden Markov Model (HMM). Traffic flow can be classified into two-states and switching between two states controlled by first-order Markov chain with a certain probability. The model is characterized by several Gaus...

We focus on the estimation of the order of a finite Markov source based on empirically observed statistics. The following performance criterion is adopted minimize the probability of underestimating the model order while keeping the overestimation probability exponent at a given prescribed level. A universal asymptotically optimal test, in the sense just defined, is proposed for the case where ...

The aim of this work is to improve the performance of lecture speech recognition by using a system combination approach. In this paper, we propose a new combination technique in which various types of acoustic models are combined. In the combination approach, the use of complementary information is important. In order to prepare acoustic models that incorporate a variety of acoustic features, w...