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

Monday 20th February 2012 – 15:45 to 16:45

Speaker: Salvador Ortiz-Latorre (Imperial College, London)

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.

Part of the Stochastic Analysis Seminar Series