Evolution of proteins:An ergodic stationary markov chain

Non-stationary fuzzy Markov chain

This paper deals with a recent statistical model based on fuzzy Markov random chains for image segmentation, in the context of stationary and non-stationary data. On one hand, fuzzy scheme takes into account discrete and continuous classes through the modeling of hidden data imprecision and on the other hand, Markovian Bayesian scheme models the uncertainty on the observed data. A non-stationar...

Ergodic Properties of Stationary, Markov, and Regenerative Processes

Linear dependence of stationary distributions in ergodic Markov decision processes

In ergodic MDPs we consider stationary distributions of policies that coincide in all but n states, in which one of two possible actions is chosen. We give conditions and formulas for linear dependence of the stationary distributions of n+2 such policies, and show some results about combinations and mixtures of policies.

analysis of ruin probability for insurance companies using markov chain

در این پایان نامه نشان داده ایم که چگونه می توان مدل ریسک بیمه ای اسپیرر اندرسون را به کمک زنجیره های مارکوف تعریف کرد. سپس به کمک روش های آنالیز ماتریسی احتمال برشکستگی ، میزان مازاد در هنگام برشکستگی و میزان کسری بودجه در زمان وقوع برشکستگی را محاسبه کرده ایم. هدف ما در این پایان نامه بسیار محاسباتی و کاربردی تر از روش های است که در گذشته برای محاسبه این احتمال ارائه شده است. در ابتدا ما نشا...

Ergodic Theory for Controlled Markov Chains with Stationary Inputs

Consider a stochastic process Γ on the finite alphabet consisting of the d standard basiselements in R. It is conditionally Markov, given a real-valued ‘input process’ ζ. This is assumedto be small, which is modeled through the scaling,ζt = εζ 1t , 0 ≤ ε ≤ 1 ,where ζ is a bounded stationary process. The following conclusions are obtained, subject tosmoothness assumpt...