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The paper presents an improved method for analog-to-digital-converter (ADC) nonlinearity correction based on a Bayesian-filtering approach. In particular, the dependence of a previous method version on the statistical characterization of the input signal has been removed. Now, the method can work on whatever stimulus signal is used without a priori knowledge about it. The proposed improvement has been validated by a numerical simulation using behavioral models provided by an ADC manufacturer and by an experiment in real ADCs.