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Reciprocal Chains: Foundations
Linköping University, Department of Mathematics, Mathematical Statistics . Linköping University, Faculty of Science & Engineering.
Linköping University, Department of Mathematics, Mathematical Statistics . Linköping University, Faculty of Science & Engineering. Eduardo Mondlane Univ, Mozambique.
Linköping University, Department of Mathematics, Mathematical Statistics . Linköping University, Faculty of Science & Engineering.
2020 (English)In: IEEE Transactions on Automatic Control, ISSN 0018-9286, E-ISSN 1558-2523, Vol. 65, no 11, p. 4840-4845Article in journal (Refereed) Published
Abstract [en]

Reciprocal processes are stochastic processes such that the current state only depends on the nearest past and future. The research on continuous-time reciprocal processes has been comprehensive since the 1970s, while surprisingly discrete-time reciprocal processes (i.e., reciprocal chains) are rarely seen in the literature. What is worse is that in the scant literature where reciprocal chains are mentioned, a misunderstanding on how to formally define reciprocal chains has existed since 2008. This article aims to formally define reciprocal chains and provide foundations for the study of them.

Place, publisher, year, edition, pages
2020. Vol. 65, no 11, p. 4840-4845
Keywords [en]
Markov processes; Mathematical model; Manganese; Process control; Graphical models; 5G mobile communication; Chapman– Kolmogorov equation; graphical models; Markov chains; reciprocal chains
National Category
Probability Theory and Statistics
Identifiers
URN: urn:nbn:se:liu:diva-171970DOI: 10.1109/TAC.2019.2958834ISI: 000583711500028OAI: oai:DiVA.org:liu-171970DiVA, id: diva2:1510446
Note

Funding Agencies|Swedish International Development Cooperation Agency

Available from: 2020-12-16 Created: 2020-12-16 Last updated: 2020-12-16

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Erhardsson, TorkelSaize, StefaneYang, Xiangfeng
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