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dc.contributor.authorVo, Ba-Ngu
dc.contributor.authorVo, Ba Tuong
dc.date.accessioned2017-01-30T13:17:09Z
dc.date.available2017-01-30T13:17:09Z
dc.date.created2015-10-29T04:09:47Z
dc.date.issued2014
dc.identifier.citationVo, B. and Vo, B. 2014. A stochastic geometric approach to sensor array processing, in Proceedings of the 2014 IEEE Workshop on Statistical Signal Processing (SSP), Jun 29-Jul 2 2014, pp. 236-239. Gold Coast, Qld, IEEE.
dc.identifier.urihttp://hdl.handle.net/20.500.11937/30044
dc.identifier.doi10.1109/SSP.2014.6884619
dc.description.abstract

A new unified mathematical framework for sensor array processing is proposed. The proposed framework combines Bayesian estimation with stochastic geometry to accommodate prior information, uncertainty in array parameters, and unknown and stochastically time-varying number of nonstationary sources. A system model for a common signal setting is constructed to demonstrate the proposed framework.

dc.publisherIEEE Computer Society
dc.titleA stochastic geometric approach to sensor array processing
dc.typeConference Paper
dcterms.source.startPage236
dcterms.source.endPage239
dcterms.source.titleIEEE Workshop on Statistical Signal Processing Proceedings
dcterms.source.seriesIEEE Workshop on Statistical Signal Processing Proceedings
dcterms.source.isbn9781479949755
curtin.departmentDepartment of Electrical and Computer Engineering
curtin.accessStatusFulltext not available


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