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A Robust Algorithm to Identify the Test Stimulus in Histogram-Based A/D Converter Testing

机译:一种基于直方图的A / D转换器测试中识别测试刺激的鲁棒算法

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摘要

Traditional testing of analog-to-digital converters (ADCs) with automatic test equipment is time-consuming and expensive, and a built-in self-test (BIST) can be one solution to this problem. Most of the proposed BIST routines require a well-known test stimulus which is much more linear than the device under test. A stimulus error identification and removal (SEIR) method that does not require a high-linearity stimulus has been proposed recently, and it is evident that reliable test results could be achieved with a stimulus linearity lower than the required measurement accuracy. This paper presents a simple and easy-to-implement calculation algorithm for use with the stimulus-identification method, particularly for BIST purposes. Simulations demonstrate that the integral-nonlinearity measuring accuracy of the SEIR method with the new calculation algorithm is 1 least significant bit for 14-b ADCs, even though the linearity of the test stimulus is only 7 b. The SEIR method and the new simpler calculation algorithm can reduce the hardware resources required for ADC BIST.
机译:使用自动测试设备对传统的模数转换器(ADC)进行传统的测试既耗时又昂贵,而内置自测(BIST)可能是解决此问题的一种方法。大多数提议的BIST例程都需要众所周知的测试刺激,它比被测设备的线性度高得多。最近,已经提出了不需要高线性刺激的刺激误差识别和消除(SEIR)方法,并且很明显,可以以低于所需测量精度的刺激线性来获得可靠的测试结果。本文提出了一种简单且易于实现的计算算法,该算法可与刺激识别方法配合使用,尤其是用于BIST的目的。仿真表明,即使测试刺激的线性仅为7 b,采用新的计算算法的SEIR方法的积分非线性测量精度对于14-b ADC也仅为1最低有效位。 SEIR方法和新的更简单的计算算法可以减少ADC BIST所需的硬件资源。

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