Prediction of the Intensity Process of Doubly Stochastic Multichannel Poisson Processes

被引：0

作者：

Maria Fernandez-Alcala, Rosa ^{[1
]}

Navarro-Moreno, Jesus ^{[1
]}

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

机构：

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

来源：

IEEE TRANSACTIONS ON AUTOMATIC CONTROL | 2012年 / 57卷 / 07期

关键词：

Doubly stochastic multichannel Poisson processes; minimum mean square-error filtering and prediction problems; LEAST-SQUARES ESTIMATION; SPECTRAL FACTORIZATION; COVARIANCE FUNCTIONS; RECURSIVE ESTIMATION; INNOVATIONS APPROACH;

D O I：

10.1109/TAC.2011.2178878

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

This paper is concerned with the problem of predicting the intensity process of an observed doubly stochastic multichannel Poisson process. Under the only hypothesis that the covariance function of the intensity process is separable, recursive algorithms for the computation of the optimal linear filter and predictor are designed. Approximate solutions to the nonlinear filtering and prediction problems are also given. The main advantage of the proposed solutions is that they can be applied to those situations where the intensity process does not satisfy a stochastic differential equation.

引用

页码：1843 / 1848

页数：6

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