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控制理论和非线性滤波讨论班
Estimation of the Linear system via Optimal Transportation and Its Application for Missing Data Observations
Estimation of the Linear system via Optimal Transportation and Its Application for Missing Data Observations
组织者
演讲者
时间
2023年03月03日 21:30 至 22:00
地点
Online
摘要
In this report, we present a unified framework for particle data fusion based on optimal transportation. The sequence data fusion can be considered as three different types, prediction problems, filtering problem and smoothing problem. We summarise the different particle methods as the paths on the Wasserstein space. However, there are infinite-many flow models corresponding to the same path. Firstly, we design the tangent flow by using the optimal transportation so that this flow model is unique, deterministic and optimal in the sense of Wasserstein space. The tangent flow of PDE can be used to solve the prediction/sampling problem. The tangent flow of SPDE can be used to solve the filtering problem. Finally, we extend the filtering algorithm as smoothing algorithm by using the forward-backward duality of Mayne–Fraser two-filter formula.