Successive-approximation analog-to-digital converter and quantitative method based on adaptive prediction interval thereof

Abstract

The invention discloses a successive-approximation analog-to-digital converter and a quantitative method based on an adaptive prediction interval thereof, and belongs to the technical field of analog-to-digital conversion. In the invention, a DAC module comprises two redundant capacitances; the quantitative method comprises the steps of switching a first redundant capacitance according to a firstcomparison result before the redundant capacitance is switched and obtaining a switched second comparison result; judging whether to continue quantification or to switch the second redundant capacitance according to a comparison of the first comparison result and the second comparison result and obtaining a switched third comparison result; and then judging whether to adjust a prediction intervalor to directly start the quantification from a highest digit according to a comparison of the second comparison result and the third comparison result. According to the successive-approximation analog-to-digital converter and the quantitative method based on the adaptive prediction interval thereof, a sampling point in a window size range of the prediction interval can be guaranteed to be predicted correctly; and through the correct prediction, the comparison times and the switching times of a capacitance switch in the DAC module can be greatly reduced.

Description

technical field [0001] The invention belongs to the technical field of analog-to-digital conversion, and in particular relates to a successive approximation analog-to-digital converter and its quantization method based on an adaptive prediction interval, and the application of the invention in extracting characteristic parameters of bioelectrical signals. Background technique [0002] In view of the fact that the amplitude of the bioelectric signal changes slowly, the distinction between different bands is obvious, and it has periodic changes in most of the time, some literatures have proposed an interval prediction algorithm. The traditional interval prediction technology directly calculates the value by a few digits higher than the last quantification result. Load the quantization results of the high digits of this time. If the prediction is correct, the low digit comparison can be performed. If the prediction is wrong, the lower plate capacitance of the high digits will be...

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Problems solved by technology

However, this interval prediction algorithm has obvious shortcomings. When the input signal sampling point is outside the prediction interval, but very close to the prediction interval, the signal amplitude of the two samples before and after the change is still very small. The interval prediction algorithm will judge that the prediction is wrong, and will predict Interval capacitance is reset and requantized, causing unnecessary comparisons and switches

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