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Graphical model depicting the hierarchical Laplacian scale mixture model’s Bayesian prior dependencies in the RWTV-DF algorithm. Prior state estimates of the signal edges are used to set the hyper-priors for the second level variables (i.e., variances of the state estimates), thereby implementing a dynamical filter that incorporates edge information into the next time step.
