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Browsing by Subject "Asymptotic optimality"

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    Correction to: Asymptotically optimal Bayesian sequential change detection and identification rules
    (2024) Dayanık, Savaş; Powell, W. B.; Yamazaki, K.
    The article Asymptotically optimal Bayesian sequential change detection and identification rules, written by Savas Dayanik, Warren B. Powell, Kazutoshi Yamazaki, was originally published electronically on the publisher’s internet portal on 12 April, 2012 without open access. With the author(s)’ decision to opt for Open Choice the copyright of the article changed on 02 Sept, 2021 to © The Author(s). Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder.
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    Detection and identification of changes of hidden Markov chains: Asymptotic theory
    (Springer Science and Business Media B.V., 2021-10-06) Dayanık, Savaş; Yamazaki, Kazutoshi
    This paper revisits a unified framework of sequential change-point detection and hypothesis testing modeled using hidden Markov chains and develops its asymptotic theory. Given a sequence of observations whose distributions are dependent on a hidden Markov chain, the objective is to quickly detect critical events, modeled by the first time the Markov chain leaves a specific set of states, and to accurately identify the class of states that the Markov chain enters. We propose computationally tractable sequential detection and identification strategies and obtain sufficient conditions for the asymptotic optimality in two Bayesian formulations. Numerical examples are provided to confirm the asymptotic optimality. © 2021, The Author(s).
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    Time delay estimation in cognitive radio systems
    (IEEE, 2009-12) Koçak, Fatih; Çelebi, H.; Gezici, Sinan; Qaraqe, K. A.; Arslan, H.; Poor, H. V.
    In cognitive radio systems, secondary users can utilize multiple dispersed bands that are not used by primary users. In this paper, time delay estimation of signals that occupy multiple dispersed bands is studied. First, theoretical limits on time delay estimation are reviewed. Then, two-step time delay estimators that provide trade-offs between computational complexity and performance are investigated. In addition, asymptotic optimality properties of the two-step time delay estimators are discussed. Finally, simulation results are presented to explain the theoretical results. © 2009 IEEE.

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