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Maximum likelihood estimation for linearity testing of ADCs stimulated by known constant signals

机译:已知常数信号激发的ADC线性测试的最大似然估计

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A maximum likelihood (ML) estimator is derived for the problem of measuring the code transition levels of an analog-to-digital converter (ADC). The proposed method is intended to test the linearity of the ADC in the static regime, using only constant test signals, except for a small amount of additive noise. The measurement data are employed in a nearly optimal manner, due to the statistical properties of the ML estimator, which are thoroughly examined. The reported analysis allows the design of the test under a given uncertainty constraint.
机译:针对测量模数转换器(ADC)的代码转换电平的问题,得出了最大似然(ML)估计器。所提出的方法旨在在静态状态下仅使用恒定的测试信号来测试ADC的线性度,除了少量的附加噪声。由于对ML估计器的统计属性进行了彻底检查,因此以几乎最佳的方式使用测量数据。报告的分析允许在给定的不确定性约束下设计测试。

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