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 is devoted to the study of determining optimal process mean in system production with the two markets for the sale of goods. in this paper, we developed an absorbing markov chain model in production systems where all items are inspected %100 for conformance with their specification limits. when the value of the quality characteristic of an item falls below a lower limit, the item is ...

Bayesian inference for the superposition of nonhomogeneous Poisson processes is studied. A Markov chain Monte Carlo method with data augmentation is developed to compute the features of the posterior distribution. For each observed failure epoch, we introduce a latent variable that indicates which component of the superposition model gives rise to the failure. This data augmentation approach fa...

The notion of infinite order Markov process is introduced and the Markov property of the flow of information is established.

By using the optimum-interval interpolation estimation, in this paper, a new composite model which is based on the improved second generation wavelet transform and second order nonhomogeneous Hidden Markov Model(ISGWT-SNHMM) is proposed and applied in the power quality disturbance classification. By adopting the interpolating scheme and the optimum-interval interpolation estimation, the predict...