This post is for providing some intuition for people who are interested in Kalman Filters, trying to learn what it is but lost their way in equations and for dummies explanations involving matrix notation! Wikipedia definition: Kalman filtering , also known as linear quadratic estimation ( LQE ), is an algorithm that uses a series of measurements observed over time, containing statistical noise and other inaccuracies, and produces estimates of unknown variables that tend to be more accurate than those based on a single measurement alone, by using Bayesian inference and estimating a joint probability distribution over the variables for each time-frame. The filter is named after Rudolf E. Kálmán , one of the primary developers of its theory. Quantopian Definition: The Kalman filter is an algorithm that uses noisy observations of a system over time to estimate the parameters of the system (some of which are unobservable) and predict future observations. At each time ste...
Signal is in the noise...