Title:
Asymptotic theory for decentralized sequential hypothesis testing problems and sequential minimum energy design algorithm

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dc.contributor.advisor Mei, Yajun
dc.contributor.author Wang, Yan en_US
dc.contributor.committeeMember Ji, Chuanyi
dc.contributor.committeeMember Shapiro, Alexander
dc.contributor.committeeMember Vengazhiyil, Roshan Joseph
dc.contributor.committeeMember Wu, C. F. Jeff
dc.contributor.department Industrial and Systems Engineering en_US
dc.date.accessioned 2011-09-22T17:47:21Z
dc.date.available 2011-09-22T17:47:21Z
dc.date.issued 2011-05-19 en_US
dc.description.abstract The dissertation investigates asymptotic theory of decentralized sequential hypothesis testing problems as well as asymptotic behaviors of the Sequential Minimum Energy Design (SMED). The main results are summarized as follows. 1.We develop the first-order asymptotic optimality theory for decentralized sequential multi-hypothesis testing under a Bayes framework. Asymptotically optimal tests are obtained from the class of "two-stage" procedures and the optimal local quantizers are shown to be the "maximin" quantizers that are characterized as a randomization of at most M-1 Unambiguous Likelihood Quantizers (ULQ) when testing M >= 2 hypotheses. 2. We generalize the classical Kullback-Leibler inequality to investigate the quantization effects on the second-order and other general-order moments of log-likelihood ratios. It is shown that a quantization may increase these quantities, but such an increase is bounded by a universal constant that depends on the order of the moment. This result provides a simpler sufficient condition for asymptotic theory of decentralized sequential detection. 3. We propose a class of multi-stage tests for decentralized sequential multi-hypothesis testing problems, and show that with suitably chosen thresholds at different stages, it can hold the second-order asymptotic optimality properties when the hypotheses testing problem is "asymmetric." 4. We characterize the asymptotic behaviors of SMED algorithm, particularly the denseness and distributions of the design points. In addition, we propose a simplified version of SMED that is computationally more efficient. en_US
dc.description.degree Ph.D. en_US
dc.identifier.uri http://hdl.handle.net/1853/41082
dc.publisher Georgia Institute of Technology en_US
dc.subject Asymptotic optimality en_US
dc.subject Quantizers en_US
dc.subject Sequential minimum energy design en_US
dc.subject Hypothesis Testing en_US
dc.subject Decentralized sequential design en_US
dc.subject.lcsh Algorithms
dc.subject.lcsh Mathematical optimization
dc.subject.lcsh Statistical hypothesis testing
dc.subject.lcsh Asymptotic efficiencies (Statistics)
dc.title Asymptotic theory for decentralized sequential hypothesis testing problems and sequential minimum energy design algorithm en_US
dc.type Text
dc.type.genre Dissertation
dspace.entity.type Publication
local.contributor.advisor Mei, Yajun
local.contributor.author Wang, Yan
local.contributor.corporatename H. Milton Stewart School of Industrial and Systems Engineering
local.contributor.corporatename College of Engineering
relation.isAdvisorOfPublication 278b2355-ca85-4111-b664-4d7e39f71482
relation.isAuthorOfPublication a38bad34-41fc-48e0-88bc-fc9e3ce89209
relation.isOrgUnitOfPublication 29ad75f0-242d-49a7-9b3d-0ac88893323c
relation.isOrgUnitOfPublication 7c022d60-21d5-497c-b552-95e489a06569
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