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Exact filters for doubly stochastic AR models with conditionally Poisson observations

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2 Author(s)
Evans, J. ; Dept. of Electr. Eng. & Comput. Sci., California Univ., Berkeley, CA, USA ; Krishnamurthy, V.

The authors derive exact filters for the state of a doubly stochastic auto-regressive (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

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Automatic Control, IEEE Transactions on  (Volume:44 ,  Issue: 4 )