## Kalman Filter

Kalman filtering (and filtering in general) considers the following setting: we have a sequence of states $x_t$, which evolves under random perturbations over time. Unfortunately we cannot observe $x_t$, we can only observe some noisy function of $x_t$, namely, $y_t$. Our task is to find the best estimate of $x_t$ given our observations of $y_t$. Continue reading “Kalman Filter”

## Notes for Stochastic Control 2019

The link below contains notes PDF for this years stochastic control course

stochastic_control_2019

I’ll upload individual posts for each section. I’ll likely update these notes and add more exercises over the coming semester. I’ll add this update in a further post at the end of the course. Comments, typos, suggestions are always welcome.

## Probability Son, Father and Grandfather have same birthday.

Here is a quick request for comments for Probability 1 students. Here are two answers saying that the probability that a grandfather, father and son are all born on the same day.

https://www.mirror.co.uk/news/uk-news/baby-boy-born-same-date-13416140