In the context of stochastic processes, the "filtering problem" refers to the challenge of estimating the internal state of a dynamic system based on noisy observations over time. More formally, it involves inferring the hidden or latent variables (states) of a system given a series of observations (measurements) that are corrupted by noise.
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