HABIST:基于直方图的模拟内置自检

A. Frisch, T. Almy
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引用次数: 50

摘要

这种基于直方图的测试方法收集节点上活动的统计表示,并使用模板直方图作为参考处理该表示。在大多数情况下,不需要特殊的刺激——数据是在被测电路工作时就地收集的。(或者,可以提供模拟刺激,例如,使用伪随机序列发生器或带有D到a转换器的存储数字矢量)。根据模板直方图处理数据的结果是压缩的人类可读签名,该签名定义了增益、偏移、噪声和失真错误。这些错误可以用来启发式地确定因果关系。本文描述了HABIST方法及其实现中的可选变化,处理直方图以获得签名和其他压缩形式的数据的算法,包括波形参数,应用该算法产生的差异直方图的示例,以及直方图生成的方法和电路。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
HABIST: histogram-based analog built in self test
This histogram based method of test collects a statistical representation of the activity at a node and processes that representation using a template histogram as a reference. In most cases, no special stimulus is required-data is collected in-situ, while the circuit under test is functioning. (Alternatively, analog stimulus, e.g. using a pseudo random sequence generator or stored digital vectors with a D to A converter, may be provided). The result of processing the data against the template histogram is a compressed human readable signature that defines gain, offset, noise, and distortion errors. These errors can then be used heuristically to determine causation. This paper describes the HABIST method and optional variations in its implementation, algorithms for processing histograms to obtain signatures and other compressed form of data, including waveform parameters, examples of the difference histograms that result from applying the algorithm, and methods and circuits for histogram generation.
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