Decentralized detection for censored binary observations with statistical dependence

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Show simple item record Lázaro Teja, Marcelino 2022-02-09T08:37:02Z 2022-02-09T08:37:02Z 2016-06
dc.identifier.bibliographicCitation Lázaro, M. (2016). Decentralized detection for censored binary observations with statistical dependence. Signal Processing, 123, 112–121.
dc.identifier.issn 0165-1684
dc.description.abstract This paper analyzes the problem of distributed detection in a sensor network of binary sensors. In particular, statistical dependence between local decisions (at binary sensors) is assumed, and two complementary methods to save energy have been considered: censoring, to avoid some transmissions from sensors to fusion center, and a sleep and wake up random schedule at local sensors. The effect of possible failures in transmission has been also included, considering the probability of having a successful transmission from a sensor to the fusion center. In this scenario, the necessary statistical information has been identified, the optimal decision rule at the fusion center has been obtained, and some examples have been used to analyze the effect of statistical dependence in a simple network with two sensors.
dc.format.extent 10
dc.language.iso eng
dc.publisher Elsevier
dc.rights © 2016 Elsevier B.V. All rights reserved.
dc.rights Atribución-NoComercial-SinDerivadas 3.0 España
dc.subject.other Wireless sensor networks
dc.subject.other Correlation
dc.subject.other Censoring
dc.subject.other Correlated local decisions
dc.subject.other Sensor networks
dc.subject.other Distributed detection
dc.subject.other Multiple sensors
dc.subject.other Gaussian-noise
dc.subject.other Fusion
dc.title Decentralized detection for censored binary observations with statistical dependence
dc.type article
dc.subject.eciencia Telecomunicaciones
dc.rights.accessRights openAccess
dc.type.version acceptedVersion
dc.identifier.publicationfirstpage 112
dc.identifier.publicationlastpage 121
dc.identifier.publicationtitle Signal Processing
dc.identifier.publicationvolume 123
dc.identifier.uxxi AR/0000017813
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