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Prediction of the Intensity Process of Doubly Stochastic Multichannel Poisson Processes

机译:双随机多通道泊松过程强度过程的预测

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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.
机译:本文涉及预测观察到的双随机多通道泊松过程强度过程的问题。在强度过程的协方差函数是可分离的唯一假设下,设计了用于计算最佳线性滤波器和预测变量的递归算法。还给出了非线性滤波和预测问题的近似解。所提出的解决方案的主要优点是可以将它们应用于强度过程不满足随机微分方程的情况。

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