Recursive integral equations for the detection of counting processes
dc.contributor.author | Beutler, Frederick J. (Frederick Joseph) | en_US |
dc.contributor.author | Dolivo,françois-Bernard | en_US |
dc.date.accessioned | 2006-09-11T19:45:41Z | |
dc.date.available | 2006-09-11T19:45:41Z | |
dc.date.issued | 1976-03 | en_US |
dc.identifier.citation | Dolivo, Francois B.; Beutler, Frederick J.; (1976). "Recursive integral equations for the detection of counting processes." Applied Mathematics & Optimization 3(1): 65-71. <http://hdl.handle.net/2027.42/48093> | en_US |
dc.identifier.issn | 1432-0606 | en_US |
dc.identifier.issn | 0095-4616 | en_US |
dc.identifier.uri | https://hdl.handle.net/2027.42/48093 | |
dc.description.abstract | A recursive stochastic integral equation for the detection of counting processes is derived from a previously known formula [5] of the likelihood ratio. This is done quite simply by using a result due to Doléans-Dade [4] on the solution of stochastic integral equations. | en_US |
dc.format.extent | 411660 bytes | |
dc.format.extent | 3115 bytes | |
dc.format.mimetype | application/pdf | |
dc.format.mimetype | text/plain | |
dc.language.iso | en_US | |
dc.publisher | Springer-Verlag; Springer-Verlag New York Inc. | en_US |
dc.subject.other | Systems Theory, Control | en_US |
dc.subject.other | Mathematical and Computational Physics | en_US |
dc.subject.other | Mathematics | en_US |
dc.subject.other | Optimization | en_US |
dc.subject.other | Calculus of Variations and Optimal Control | en_US |
dc.subject.other | Numerical and Computational Methods | en_US |
dc.subject.other | Mathematical Methods in Physics | en_US |
dc.title | Recursive integral equations for the detection of counting processes | en_US |
dc.type | Article | en_US |
dc.subject.hlbsecondlevel | Mathematics | en_US |
dc.subject.hlbtoplevel | Science | en_US |
dc.description.peerreviewed | Peer Reviewed | en_US |
dc.contributor.affiliationum | Information and Control Engineering Program, The University of Michigan, 48109, Ann Arbor, Michigan, USA | en_US |
dc.contributor.affiliationother | IBM Research Laboratory, Zurich, Switzerland; IBM Forschung Laboratorium, CH 8803, Rüschlitnou, Switzerland | en_US |
dc.contributor.affiliationumcampus | Ann Arbor | en_US |
dc.description.bitstreamurl | http://deepblue.lib.umich.edu/bitstream/2027.42/48093/1/245_2005_Article_BF02106191.pdf | en_US |
dc.identifier.doi | http://dx.doi.org/10.1007/BF02106191 | en_US |
dc.identifier.source | Applied Mathematics & Optimization | en_US |
dc.owningcollname | Interdisciplinary and Peer-Reviewed |
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