inhomogeneous markov chain
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Mathematics ◽  
2022 ◽  
Vol 10 (2) ◽  
pp. 251
Author(s):  
Virginia Giorno ◽  
Amelia G. Nobile

We consider a time-inhomogeneous Markov chain with a finite state-space which models a system in which failures and repairs can occur at random time instants. The system starts from any state j (operating, F, R). Due to a failure, a transition from an operating state to F occurs after which a repair is required, so that a transition leads to the state R. Subsequently, there is a restore phase, after which the system restarts from one of the operating states. In particular, we assume that the intensity functions of failures, repairs and restores are proportional and that the birth-death process that models the system is a time-inhomogeneous Prendiville process.


Author(s):  
E. A. Perepelkin ◽  

The problem of constructing a state estimation of inhomogeneous finite Markov chain based on a Luenberger observer is solved. The conditions of existence of the observer are defined. An algorithm for synthesizing the observer is described.


Mathematics ◽  
2020 ◽  
Vol 8 (2) ◽  
pp. 174
Author(s):  
Vitaliy Golomoziy ◽  
Yuliya Mishura

This paper is devoted to the study of the stability of finite-dimensional distribution of time-inhomogeneous, discrete-time Markov chains on a general state space. The main result of the paper provides an estimate for the absolute difference of finite-dimensional distributions of a given time-inhomogeneous Markov chain and its perturbed version. By perturbation, we mean here small changes in the transition probabilities. Stability estimates are obtained using the coupling method.


2018 ◽  
Vol 33 (4) ◽  
pp. 579-590
Author(s):  
Wenxi Li ◽  
Zhongzhi Wang

AbstractIn this note, we use the Perron–Frobenius theorem to obtain the Rényi's entropy rate for a time-inhomogeneous Markov chain whose transition matrices converge to a primitive matrix. As direct corollaries, we also obtain the Rényi's entropy rate for asymptotic circular Markov chain and the Rényi's divergence rate between two time-inhomogeneous Markov chains.


2018 ◽  
Vol 2018 (1) ◽  
Author(s):  
Yun Dong ◽  
Fang-qing Ding ◽  
Qi-feng Yao

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