A particle filter, also known as sequential Monte Carlo (SMC) methods, is a technique used in statistical estimation and tracking processes. It is particularly effective for estimating the state of a dynamic system that is governed by a non-linear model and subject to non-Gaussian noise. Particle filters are widely used in fields such as robotics, computer vision, signal processing, and econometrics.
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