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A behavioral representation of Nyquist data converters is presented. The representation captures the static behavior of a memoryless Nyquist data converter including statistical variations. The variations are classified into noise and process variations according to how these nonidealities affect the converter behavior. To describe noise effects, a joint probability density function is used. To describe behavioral effects due to process variations, a Gaussian model is used. Using the behavioral representation, a novel strategy to calculate system performance is developed. The performance specifications of a converter, including offset error, full scale gain error, integral nonlinearity, differential nonlinearity, harmonic distortion, and signal-to-noise ratio, are calculated in two steps. First, the converter model parameters are extracted from the circuit. Then, the converter performance is computed using only the model parameters since the model captures the converter behavior. Experimental results agree well with SPICE simulations and confirm the validity of the model.>
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Liu et al. (1995) studied this question.
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