Importance

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Abstract

Errors in a sampled data process are discerned statistically throughout the process, permitting their efficient removal. An exemplary application is a subranging analog-to-digital converter (ADC), in which errors associated with component digital-to-analog (DAC) current sources are discerned and corrected automatically during the circuit's normal operation. This is achieved by continually introducing a random signal into the process, statistically examining the DAC output signal to discern error terms, and correlating the occurrences of these errors with the values of the random signal applied to the DACs so as to identify the current sources to which the error terms are due. The resulting ADC output signal is compensated to remove the random signal and is further compensated to remove the DAC error terms discerned by this statistical analysis. The effect of any errors that may remain due to imperfect quantification of the DAC error terms is minimized due to their randomization, permitting the removal of these error terms by averaging techniques.

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First Claim