Exact filters for doubly stochastic AR models with conditionally Poisson observations

被引：3
|
作者：
Evans, J [1 ]
Krishnamurthy, V
机构：
[1] Univ Calif Berkeley, Dept Elect Engn & Comp Sci, Berkeley, CA 94720 USA
[2] Univ Melbourne, Dept Elect & Elect Engn, Parkville, Vic 3052, Australia
来源：
IEEE TRANSACTIONS ON AUTOMATIC CONTROL | 1999年 / 44卷 / 04期
基金：
澳大利亚研究理事会;
关键词：
doubly stochastic models; exact filters; nonlinear filters; Poisson observations;
D O I：
10.1109/9.754820
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
In this paper 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.
引用
收藏
页码：794 / 798
页数：5
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