Abstract

This paper presents a behavioral representation for the class of Nyquist rate A/D converters that captures the nominal behavior, as well as all the statistical variations. To describe noise effects we use a joint probability density function. To describe behavioral effects due to process variations we use a covariance matrix, \Sigma t . Applications of the model include identification of important A/D error sources, efficient computation of the distributions of integral nonlinearity (INL) and differential nonlinearity (DNL), signal-to-noise plus distortion ratio (TSNR), and efficient worst case and Monte Carlo system simulations. Finally, parameter extraction results are presented that agree well with actual measurements. 1 Introduction The verification of data converters poses a significant challenge to the design community, partly due to the need for higher yield at high resolutions, and partly due to the emphasis on predicting converter performance when used in a system since more ...

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