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For a class of non-uniformly ergodic Markov chains (X  n ) satisfying exponential or polynomial beta-mixing, under observations (Y  n ) subject to an IID noise with a positive density, it is shown that wrong initial data is forgotten in the mean total variation topology, with a certain exponential or polynomial rate.

On discrete time ergodic filters with wrong initial data