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An adaptive BIST for INL estimation of ADCs without histogram evaluation

机译:无需直方图评估即可用于ADC的INL估计的自适应BIST

摘要

A robust low-cost test solution for static characterization of analog-to-digital converters (ADCs) is presented in this paper. It uses an adaptive algorithm to perform a blind and accurate estimation of the Integral Non-Linearity (INL) of the ADC under test (ADCUT). Its main applications are for: a) simple off-line ADC test using modern mixed-signal ATEs (Automatic Test Equipments) without requiring any dedicated input stimulus, b) Built-in Self-test (BIST) for ADC INL evaluation either in concurrent (on-line) or non-concurrent (off-line) modes. The test validation has been performed through realistic behavioral simulations including noise, mismatch and non-linear errors. Experimental results for a custom-designed 10-bit Successive Approximation (SAR) ADC are also reported.
机译:本文提出了一种用于模数转换器(ADC)静态表征的鲁棒低成本测试解决方案。它使用自适应算法对被测ADC(ADCUT)的积分非线性(INL)进行盲目且准确的估计。它的主要应用是:a)使用现代混合信号ATE(自动测试设备)的简单离线ADC测试,不需要任何专用的输入激励,b)内置自测(BIST)用于同时进行ADC INL评估(在线)或非并发(离线)模式。通过真实的行为模拟(包括噪声,失配和非线性误差)进行了测试验证。还报告了定制设计的10位逐次逼近(SAR)ADC的实验结果。

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