Join Pani W. Fernando's course "Introduction to Nonlinear Filtering Theory toward Particle Filtering" from May 15 to 18.
Pani W. Fernando is senior lecturer at University of Sri Jayewardenepura, Sri Lanka.
The course will be given in English on zoom.
This is a recurrent meeting, so please register only once for all 4 sessions:
https://zoom.us/meeting/register/tJcldOuppjIpGNNliClqvaXYFEJG7p2397Q1#/…
The course will take place on the following days (Paris time zone):
- Monday 15 May: 10:00am - 12:00am
- Tuesday 16 May: 10:00am - 12:00am
- Wednesday 17 May: 10:00am - 12:00am
- Thursday 18 May: 10:00am - 12:00am
Abstract:
Nonlinear filtering is one of the main approaches to tackle many problems involving with fields such as financial mathematics, engineering sciences, fluid dynamics, physics, etc. Unfortunately, it is impossible to obtain analytical solutions for most of the stochastic nonlinear filtering models associated with the practical problems arising in the abovementioned fields, excepting a small number of simple cases. Particle filtering plays an important role to solve such stochastic nonlinear filtering models numerically. In this short course, we are going to provide an introductory knowledge on nonlinear filtering theory and associated particle filtering approach. First, we will define the nonlinear filtering problem and then, step by step, we will discuss the necessary tools (such as conditional expectation, Bayes formula, normalized and unnormalized conditional measures, Novikov’s condition, Girsanov transformation, Kallianpur-Striebel formula, etc.) to derive the measure-valued filtering equations known as Zakai equation and FKK equation. Then we will discuss a couple of particle filtering algorithms such as Monte-Carlo method, branching particle method, etc.
Please note that the CIMPA/ICTP courses will be recorded and broadcasted on our Youtube channel "CIMPA Math" and on carmin.tv.
CIMPA does not provide certificates of attendance for online courses.
This course will be filmed at ICTP (Italy, France).