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Recursive nonlinear estimation of random parameter AR models with Poisson observations

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2 Author(s)
Evans, J.S. ; Dept. of Electr. & Electron. Eng., Melbourne Univ., Parkville, Vic., Australia ; Krishnamurthy, V.

We derive exact filters for the state of a doubly stochastic AR process with parameters which vary according to a nonlinear function of a Gauss-Markov process. The observations consist of a discrete time Poisson process with rate a positive function of the Gauss-Markov process. The dimension of the sufficient statistic increases linearly with the number of observed events

Published in:

Decision and Control, 1997., Proceedings of the 36th IEEE Conference on  (Volume:5 )

Date of Conference:

10-12 Dec 1997

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