Improved Estimate of Parametric Models for Analogue to Digital Converters by Using Weighted Integral Nonlinearity Data
نویسندگان
چکیده
Error modelling has played a major role in generating post-corrections of analogue to digital converters (ADC). Benefits by using parametric models for post-correction are that they requires less memory and that they are easier to identify for arbitrary signals. However, the parameters are estimated in two steps; firstly, the integral nonlinearity (INL) is estimated and secondly, the model parameters. In this paper we propose a method to improve the performance in the second step, by utilizing information about the statistical properties of the first step.
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