a profile hidden markov model (phmm) is widely used in assigning protein sequences to protein families. in this model, the hidden states only depend on the previous hidden state and observations are independent given hidden states. in other words, in the phmm, only the information of the left side of a hidden state is considered. however, it makes sense that considering the information of the b...

Mixed Presence Groupware (MPG) is software that connects collocated and distributed collaborators together in a shared visual workspace. The problem is that collaborators in MPG focus their collaborative energies almost exclusively on their collocated partners, ignoring their distributed counterparts. This arises because remote collaborators are disembodied when compared to their collocated coh...

We study the entropy rate of a hidden Markov process, defined by observing the output of a symmetric channel whose input is a first order Markov process. Although this definition is very simple, obtaining the exact amount of entropy rate in calculation is an open problem. We introduce some probability matrices based on Markov chain's and channel's parameters. Then, we try to obtain an estimate ...

This paper investigates the asymmetric effects of monetary policy on economic growth over business cycles in Iran. Estimating the models using the Hamilton (1989) Markov-switching model and by employing the data for 1960-2012, the results well identify two regimes characterized as expansion and recession. Moreover, the results show that an expansionary monetary policy has a positive and statist...

Large surfaces such as tabletop and whiteboard displays naturally afford collocated collaboration, where multiple people work together over the shared workspace. As large digital displays become more ubiquitous, it becomes increasingly important to examine their role in supporting groups of distributed collaborators working over the digital work surface. In particular, Mixed Presence Groupware ...

In this paper, we show that the Chapman-Kolmogorov formula could be used as a recursive formula for computing the m-step-ahead conditional density of a Markov bilinear model. The stationary marginal probability density function of the model may be approximated by the m-step-ahead conditional density for sufficiently large m.

  Stochastic models such as mixture models, graphical models, Markov random fields and hidden Markov models have key role in probabilistic data analysis. In this paper, we have learned Gaussian mixture model to the pixels of an image. The parameters of the model have estimated by EM-algorithm.   In addition pixel labeling corresponded to each pixel of true image is made by Bayes rule. In fact, ...

Improving phoneme recognition has attracted the attention of many researchers due to its applications in various fields of speech processing. Recent research achievements show that using deep neural network (DNN) in speech recognition systems significantly improves the performance of these systems. There are two phases in DNN-based phoneme recognition systems including training and testing. Mos...