Convolutional Bayesian Filtering

arXiv:2404.00481v1 Announce Type: cross
Abstract: Bayesian filtering serves as the mainstream framework of state estimation in dynamic systems. Its standard version utilizes total probability rule and Bayes' law alternatively, where how to define and compute conditional probability is critical to state distribution inference. Previously, the conditional probability is assumed to be exactly known, which represents a measure of the occurrence probability of one event, given the second event. In this paper, we find that by adding an additional event that …

abstract arxiv bayes bayesian compute cs.lg cs.sy distribution dynamic eess.sy filtering framework inference law probability standard state stat.ml systems total type