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dc.contributor.author |
Bunch, Pete |
|
dc.contributor.author |
Murphy, James |
|
dc.contributor.author |
Godsill, Simon |
|
dc.date.accessioned |
2019-07-03T13:02:21Z |
|
dc.date.available |
2019-07-03T13:02:21Z |
|
dc.date.issued |
2016-08 |
|
dc.identifier.issn |
1053587X |
|
dc.identifier.uri |
http://hdl.handle.net/123456789/7583 |
|
dc.description |
p.4100 - 4112 |
en_US |
dc.language.iso |
en |
en_US |
dc.relation.ispartofseries |
In : IEEE transactions on signal processing, Vol.64, n°16 (Aout 2016); |
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dc.subject |
Traitement du signal |
en_US |
dc.subject |
Matrices de covariance |
en_US |
dc.subject |
Apprentissage (intelligence artificielle) |
en_US |
dc.subject |
Processus de Markov |
en_US |
dc.subject |
Processus gaussiens |
en_US |
dc.subject |
Monte Carlo , méthodes de |
en_US |
dc.title |
Bayesian learning of degenerate linear gaussian state space models using markov chain monte carlo |
en_US |
dc.type |
Article |
en_US |
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