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dc.contributor.authorAdams, M.
dc.contributor.authorVo, Ba-Ngu
dc.contributor.authorMahler, R.
dc.date.accessioned2017-01-30T10:55:48Z
dc.date.available2017-01-30T10:55:48Z
dc.date.created2015-05-22T08:32:19Z
dc.date.issued2014
dc.identifier.citationAdams, M. and Vo, B. and Mahler, R. 2014. Advances in probabilistic modeling: Applications of stochastic geometry. IEEE Robotics and Automation Magazine. 21 (2): pp. 21-24.
dc.identifier.urihttp://hdl.handle.net/20.500.11937/6826
dc.identifier.doi10.1109/MRA.2014.2314018
dc.publisherInstitute of Electrical and Electronics Engineers
dc.titleAdvances in probabilistic modeling: Applications of stochastic geometry
dc.typeJournal Article
dcterms.source.volume21
dcterms.source.number2
dcterms.source.startPage21
dcterms.source.endPage24
dcterms.source.issn10709932
dcterms.source.titleIEEE Robotics and Automation Magazine
curtin.departmentDepartment of Electrical and Computer Engineering
curtin.accessStatusOpen access via publisher


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