Abstract: A system and method calibrate a redundant number system analog-to-digital converter (RNS ADC) using successive approximations of multiple input signals and approximating each input signal at least twice. The RNS ADC includes N analog converter reference elements, each of the analog converter reference elements is associated with a weight in a weight vector W, and N is an integer greater than one. The system and method successively approximate each of M distinct analog input signals twice to generate M respective pairs of successive approximation converter reference element vectors, C1j and C2j,that correspond to digital approximations of the input signals, wherein j ? {0, 1, . . . , M?1}, wherein M is a positive integer. The system and method utilize differences between the successive approximation converter reference element vectors, C1j and C2j to determine a final weight vector WB.

Abstract: Methods and apparatus are provided for reducing nonlinearities in an analog-to-digital signal converter. An analog pseudo-random noise sample is added to an analog input sample and the combined sample is converted into a digital representation. A pseudo-random digital sample corresponding to the analog noise sample is subtracted from the converted digital representation. Preferably, multiple analog noise samples are added to the analog input sample, converted and corresponding digital noise samples subtracted from the converted digital representation. The multiple digital representations are then averaged, thereby nullifying differential nonlinearities in various portions of the transfer characteristics curve of the signal converter and reducing the effects of the DNL.