Recursive linear estimation for doubly stochastic Poisson processes

被引：0

作者：

Fernandez-Alcala, Rosa ^{[1
]}

Navarro-Moreno, Jess ^{[1
]}

Ruiz-Molina, Juan Carlos ^{[1
]}

Oya, Antonia ^{[1
]}

机构：

[1] Univ Jaen, Dept Stat & Operat Res, Jaen 23071, Spain

来源：

WORLD CONGRESS ON ENGINEERING 2007, VOLS 1 AND 2 | 2007年

关键词：

doubly stochastic Poisson processes; linear minimum mean-square error estimate;

D O I：

暂无

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

The problem of estimating the intensity process of a doubly stochastic Poisson process is analyzed. Using covariance information, a recursive linear minimum mean-square error estimate is designed. Moreover, an efficient procedure for the computation of its associated error covariance is shown. The proposed solution becomes an alternative approach to the Kalman filter which is applicable under the only structural assumption that the intensity process to be estimated has a finite-dimensional covariance function.

引用

页码：894 / 897

页数：4

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