A Fast Maximum Likelihood Estimation for High-Resolution ADC Test

Cheng Huang, Guojiao Wang, Weiguang Yang

Abstract

With the increasing resolution of analog to digital converter (ADC), the percentage of the test cost in the overall chip cost is improving gradually. Therefore, faster and more accurate test methods are required urgently for the high-resolution ADC nowadays. Compared with the least squares(LS) method, the maximum likelihood(ML) estimation method can extract more information from output codes, and estimators of measured parameters are consistent and asymptotically efficient. Due to the ADC resolution is increasing, the number of transition levels raise exponentially which causes huge test parameters space. The traditional ML estimation method can’t tackle the situation of the highresolution ADC. This paper focuses on the problems of how to reduce the computation complexity and implement high-resolution ADC test with ML estimation method. The main finding is that the proposed method reduced test time in comparison of the traditional ML method. And it makes the ML estimation method use in high-resolution ADC test.

Keywords

sinewave fitting,maximum likelihood estimation(ML),parameter spectral estimation, differential evolution (DE)

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IMEKO-TC4-2014-228.pdf

DOI

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IMEKO TC

TC4 - Measurement of Electrical Quantities

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