Non-Monotonic Decision Rules for Sensor Fusion

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dc.contributor.authorMcKendall, Raymond
dc.contributor.authorMintz, Max L
dc.date2023-05-17T01:19:03.000
dc.date.accessioned2023-05-22T12:57:51Z
dc.date.available2023-05-22T12:57:51Z
dc.date.issued1990-08-01
dc.date.submitted2007-08-23T11:25:32-07:00
dc.description.abstractThis article describes non-monotonic estimators of a location parameter from a noisy measurement Z = Ɵ + V when the possible values of e have the form (0, ± 1, ± 2,. . . , ± n}. If the noise V is Cauchy, then the estimator is a non-monotonic step function. The shape of this rule reflects the non-monotonic shape of the likelihood ratio of a Cauchy random variable. If the noise V is Gaussian with one of two possible scales, then the estimator is also a nonmonotonic step function. The shape this rule reflects the non-monotonic shape of the likelihood ratio of the marginal distribution of Z given Ɵ under a least-favorable prior distribution.
dc.description.commentsUniversity of Pennsylvania Department of Computer and Information Science Technical Report No. MS-CIS-90-56.
dc.identifier.urihttps://repository.upenn.edu/handle/20.500.14332/7516
dc.legacy.articleid1605
dc.legacy.fulltexturlhttps://repository.upenn.edu/cgi/viewcontent.cgi?article=1605&context=cis_reports&unstamped=1
dc.source.issue574
dc.source.journalTechnical Reports (CIS)
dc.source.statuspublished
dc.subject.otherGRASP
dc.titleNon-Monotonic Decision Rules for Sensor Fusion
dc.typeReport
digcom.identifiercis_reports/574
digcom.identifier.contextkey349463
digcom.identifier.submissionpathcis_reports/574
digcom.typereport
dspace.entity.typePublication
relation.isAuthorOfPublication044f233a-9f29-4855-8b33-634942969424
relation.isAuthorOfPublication.latestForDiscovery044f233a-9f29-4855-8b33-634942969424
upenn.schoolDepartmentCenterTechnical Reports (CIS)
upenn.schoolDepartmentCenterGeneral Robotics, Automation, Sensing and Perception Laboratory
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