Bayesian Filter

A Bayesian filter is a method used to improve estimates of a system's state by combining prior knowledge with new observations, updating beliefs as new data arrives. It uses Bayes' theorem to calculate the probability of different states based on past information and current evidence. This approach is common in applications like tracking objects, filtering noise from signals, and predicting outcomes, enabling more accurate and reliable decisions by continuously refining the system's understanding as more data becomes available.