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Seminar Information

Title: Prediction, filtering and smoothing for doubly-stochastic cluster processes
Date: Thu 26 Nov 2009
Time: 11:00
Location: EM 2.33
Speaker: Anthony Swain
Description: In the spatio-temporal point process theory community, there is considerable interest in estimating the intensity function of a point process for various applications in epidemiology, forestry, and rainfall modeling. In the aerospace and signal processing communities, Bayesian filtering methods for propagating this intensity function, known as Probability Hypothesis Density (PHD) filters, have had a transformational effect on the development of mathematically principled target tracking algorithms, though these approaches have not received widespread attention in the spatio-temporal point process community. In this talk we describe the solution for the propagating of the intensity function of general cluster point processes that are motivated by applications in group target tracking.

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