A new approximation algorithm to solve the filtering problem combining Cubature and TBBA

Stochastic Analysis Seminar Series

In this talk we will introduce a new particle approximation scheme to solve the stochastic filtering problem. This new scheme makes use of the Kusuoka-Lyons-Victoir (KLV) method to approximate the dynamics of the signal. In order to control the computational cost, a partial sampling procedure based on the tree based branching algorithm (TBBA) is performed. The novelty of the method lies in the fact that the weights used in the TBBA are computed combining the cubature weights and the filtering weights. In this way, we can avoid the sample degeneracy problem inherent to particle filters. We will also present some simulations showing the performance of the method.


Salvador Ortiz-Latorre (Imperial College, London)

Monday, February 20, 2012 - 15:45
to 16:45