research-article

Distributed Bayesian signal detection

Authors:

I. Y. Hoballah,

P. K. VarshneyAuthors Info & Claims

IEEE Transactions on Information Theory, Volume 35, Issue 5

Pages 995 - 1000

https://doi.org/10.1109/18.42208

Published: 01 September 2006 Publication History

Abstract

The signal detection problem is considered for the case in which distributed sensors are used and a global decision is desired. Local decisions from the sensors are fed to a data fusion center, which yields a global decision based on a fusion rule. A Bayesian formulation of the problem is considered, and a person-by-person optimization of the overall system is carried out. The special case of identical detectors with independent observations is considered as well. An illustrative example is presented

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Shaska JMitra U(2022)Information Structures for State-Dependent Decentralized Detection2022 IEEE International Symposium on Information Theory (ISIT)10.1109/ISIT50566.2022.9834384(2702-2707)Online publication date: 26-Jun-2022
https://dl.acm.org/doi/10.1109/ISIT50566.2022.9834384
Wahdan MAltınkaya M(2022)Maximum average entropy-based quantization of local observations for distributed detectionDigital Signal Processing10.1016/j.dsp.2022.103427123:COnline publication date: 30-Apr-2022
https://dl.acm.org/doi/10.1016/j.dsp.2022.103427
Mages TAlmgren MRohner C(2022)Towards an information-theoretic framework of intrusion detection for composed systems and robustness analysesComputers and Security10.1016/j.cose.2022.102633116:COnline publication date: 1-May-2022
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IEEE Transactions on Information Theory Volume 35, Issue 5

September 1989

223 pages

ISSN:0018-9448

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IEEE Press

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Published: 01 September 2006

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Shaska JMitra U(2022)Information Structures for State-Dependent Decentralized Detection2022 IEEE International Symposium on Information Theory (ISIT)10.1109/ISIT50566.2022.9834384(2702-2707)Online publication date: 26-Jun-2022
https://dl.acm.org/doi/10.1109/ISIT50566.2022.9834384
Wahdan MAltınkaya M(2022)Maximum average entropy-based quantization of local observations for distributed detectionDigital Signal Processing10.1016/j.dsp.2022.103427123:COnline publication date: 30-Apr-2022
https://dl.acm.org/doi/10.1016/j.dsp.2022.103427
Mages TAlmgren MRohner C(2022)Towards an information-theoretic framework of intrusion detection for composed systems and robustness analysesComputers and Security10.1016/j.cose.2022.102633116:COnline publication date: 1-May-2022
https://dl.acm.org/doi/10.1016/j.cose.2022.102633
Shaska JMitra U(2021)Decentralized Decision-Making for Multi-Agent Networks: the State-Dependent Case2021 IEEE Global Communications Conference (GLOBECOM)10.1109/GLOBECOM46510.2021.9685149(01-06)Online publication date: 7-Dec-2021
https://dl.acm.org/doi/10.1109/GLOBECOM46510.2021.9685149
Seo DRaman RVarshney L(2020)Social Learning with Beliefs in a Parallel Network2020 IEEE International Symposium on Information Theory (ISIT)10.1109/ISIT44484.2020.9174359(1265-1270)Online publication date: 21-Jun-2020
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Chen KNatarajan B(2016)Evaluating Node Reliability in Cooperative MIMO NetworksIEEE Transactions on Information Forensics and Security10.1109/TIFS.2016.253284111:7(1453-1460)Online publication date: 1-Jul-2016
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Bays MShende AStilwell D(2016)Multi-agent motion planning using Bayes riskRobotics and Autonomous Systems10.1016/j.robot.2016.07.00986:C(1-12)Online publication date: 1-Dec-2016
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Hosseini HRaahemifar KSyed Yusof SAnpalagan A(2015)Cooperative spectrum sensing for cognitive heterogeneous networking using iterative Gauss-Seidel processInternational Journal of Distributed Sensor Networks10.1155/2015/3191642015(7-7)Online publication date: 1-Jan-2015
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Banavar MZhang JChakraborty BKwon HLi YJiang HSpanias ATepedelenlioglu CChakrabarti CPapandreou-Suppappola A(2015)An overview of recent advances on distributed and agile sensing algorithms and implementationDigital Signal Processing10.1016/j.dsp.2015.01.00139:C(1-14)Online publication date: 1-Apr-2015
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Eritmen KKeskinoz M(2014)Distributed decision fusion over fading channels in hierarchical wireless sensor networksWireless Networks10.1007/s11276-013-0649-y20:5(987-1002)Online publication date: 1-Jul-2014
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Bayesian Sparse Signal Detection Exploiting Laplace Prior

New results on the performance of distributed Bayesian detection systems

Bayesian data fusion for distributed target detection in sensor networks

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