Bayesian formulation of nonlinear filters and their electronic implementation

Fundamental nonlinear filters including Mfilters and order statistic filters are formulated generally by the maximum a-posteriori (MAP) estimation and some filters are derived with the aid of the Bayes formula. This MAP-filters reduces to M-filters if a-priori probability distribution is uniform, while the rank filters are derived when a-priori bias exists in the MAP estimation. This MAP-filters are implemented with an analog electronic circuit and the log-likelihood is shown to be a Liapunov function for the dynamics of this circuit.