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Test Generation Algorithm for Fault Detection of Analog Circuits Based on Extreme Learning Machine

机译:基于极限学习机的模拟电路故障检测测试生成算法

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摘要

This paper proposes a novel test generation algorithm based on extreme learning machine (ELM), and such algorithm is cost-effective and low-risk for analog device under test (DUT). This method uses test patterns derived from the test generation algorithm to stimulate DUT, and then samples output responses of the DUT for fault classification and detection. The novel ELM-based test generation algorithm proposed in this paper contains mainly three aspects of innovation. Firstly, this algorithm saves time efficiently by classifying response space with ELM. Secondly, this algorithm can avoid reduced test precision efficiently in case of reduction of the number of impulse-response samples. Thirdly, a new process of test signal generator and a test structure in test generation algorithm are presented, and both of them are very simple. Finally, the abovementioned improvement and functioning are confirmed in experiments.
机译:本文提出了一种基于极限学习机(ELM)的新型测试生成算法,该算法对于模拟被测设备(DUT)具有成本效益高,风险低的特点。此方法使用从测试生成算法派生的测试模式来激励DUT,然后对DUT的输出响应进行采样以进行故障分类和检测。本文提出的新颖的基于ELM的测试生成算法主要包含三个方面的创新。首先,该算法通过使用ELM对响应空间进行分类,从而有效地节省了时间。其次,在减少脉冲响应样本数量的情况下,该算法可以有效避免测试精度的降低。第三,给出了测试信号发生器的新过程和测试生成算法中的测试结构,两者都很简单。最后,在实验中证实了上述改进和功能。

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