On Algorithms for Computing Stochastic Bounds of Markov Chains with Irreducibility and Lumpability

摘要：

　　We consider algorithms for discrete-time Markov chains with finitely many states,using the LIMSUB algorithm as a representative example.The algorithms are designed to generate stochastically bounded Markov chains with the irreducibility property so long as the provided Markov chain is irreducible.Furthermore,it is possible via the described algorithms to make the stochastically bounded Markov chain lumpable,which allows reducing the size of the state space of the bounded Markov chain.Although these properties simplify the analysis of large Markov chains,the calculated stochastic bounds are high as a consequence of keeping the chains irreducible and lumpable simultaneously.In this paper,we propose a method to improve the bounds of the Markov chains.

关键词： Finite Markov chains Irreducibility Lumpability Stochastic bounds

作者: Shin’ya Ishikawa Ken’ichi Kawanishi

作者单位: Graduate School of Science and Technology,Gunma University 1-5-1 Tenjin-cho,Kiryu,Gunma 376-8515,Jap Division of Electronics and Informatics,Gunma University1-5-1 Tenjin-cho,Kiryu,Gunma 376-8515,Japan

会议类型: 国际会议

会议名称: The 12th International Conference on Queueing Theory and Network Applications(第十二届排序理论与网络应用国际会议)(QTNA 2017)

会议地点: 河北秦皇岛

会议语种:英文

页码: 70-73

在线出版日期: 2017-08-21（万方平台首次上网日期，不代表论文的发表时间）