A. Baccigalupi et al., ERROR COMPENSATION OF A D CONVERTERS USING NEURAL NETWORKS/, IEEE transactions on instrumentation and measurement, 45(2), 1996, pp. 640-644
This paper describes a new technique for compensating errors in Analog
-to-Digital Converters (ADC's), It can be considered an improvement of
the phase plane compensation technique: the idea is to exploit the ge
neralization capabilities of Artificial Neural Networks (ANN's) to red
uce the large number of experiments required. The ANN is built and set
up in a simulation environment using an ADC behavioral model, whose e
rrors can be fixed to known values, It is thus possible to simulate a
set of ADC's with very different performances, thereby enabling the us
efulness of the proposed approach to be investigated in very different
working conditions, The results were analyzed by comparing the behavi
or of uncompensated and compensated ADC outputs.