一种考虑屏蔽效应的电路输入向量敏感性计算方法
发布时间：2018-11-14 17:45
【摘要】：输入向量敏感性的计算在电路的高可靠设计过程中有着重要的实际意义,尤其是针对有着特定应用场景的电路产品.该文以概率转移矩阵模型为主要技术手段,首先简要分析了输入向量对电路故障的"驱赶"作用,接着基于屏蔽机理构建了针对电路基本构件的三种屏蔽效应的量化模型,然后利用混合编码并通过虚拟法构建的电路基本构件输出端的可观察敏感性输入向量实现了输入向量敏感性的迭代传播,再结合范数理论计算了电路输入向量的敏感性.理论分析与实验结果表明,该文所提方法的计算精度与同类型方法相似,但计算速度要快2～6倍,内存开销稍小,计算过程则更为灵巧与简便,是一种可操作性强的有效计算模型,其时空复杂性与电路中的基本构件数目成线性增长的关系.此外,实验发现输入向量的敏感性随电路基本构件故障概率的增大而增大,且电屏蔽效应与锁存窗屏蔽效应对输入向量敏感性的影响也随电路基本构件故障概率的增大而呈现出增强的趋势,电屏蔽效应尤甚.
[Abstract]:The calculation of input vector sensitivity is of great practical significance in the process of high reliability design of circuits, especially for circuit products with specific application scenarios. In this paper, the probabilistic transfer matrix model is used as the main technical means. Firstly, the function of input vector to drive the circuit fault is briefly analyzed. Then, based on the shielding mechanism, a quantitative model of three kinds of shielding effects for the basic components of the circuit is constructed. Then the iterative propagation of the input vector sensitivity is realized by using the observable sensitivity input vector of the output end of the basic component of the circuit constructed by mixed coding and virtual method. Then the sensitivity of the input vector is calculated by combining the norm theory. The theoretical analysis and experimental results show that the accuracy of the proposed method is similar to that of the same type of method, but the computational speed is 2 ~ 6 times faster, the memory cost is slightly smaller, and the calculation process is more dexterous and simple. It is an efficient and operable computing model, whose space-time complexity increases linearly with the number of basic components in the circuit. In addition, it is found that the sensitivity of the input vector increases with the increase of fault probability of the basic components of the circuit. The influence of electric shielding effect and latch window shielding effect on the sensitivity of input vector is also increasing with the increase of fault probability of the basic components of the circuit, especially the electric shielding effect.
【作者单位】： 浙江工业大学计算机科学与技术学院 同济大学软件学院
【基金】：国家自然科学基金(61502422,61432017,61374152,61773348,61374094) 浙江省自然科学基金(LY18F020028,LQ15F020006,LY17F030016,Y18F030084)资助~~
【分类号】：TP331
本文编号：2331862
[Abstract]:The calculation of input vector sensitivity is of great practical significance in the process of high reliability design of circuits, especially for circuit products with specific application scenarios. In this paper, the probabilistic transfer matrix model is used as the main technical means. Firstly, the function of input vector to drive the circuit fault is briefly analyzed. Then, based on the shielding mechanism, a quantitative model of three kinds of shielding effects for the basic components of the circuit is constructed. Then the iterative propagation of the input vector sensitivity is realized by using the observable sensitivity input vector of the output end of the basic component of the circuit constructed by mixed coding and virtual method. Then the sensitivity of the input vector is calculated by combining the norm theory. The theoretical analysis and experimental results show that the accuracy of the proposed method is similar to that of the same type of method, but the computational speed is 2 ~ 6 times faster, the memory cost is slightly smaller, and the calculation process is more dexterous and simple. It is an efficient and operable computing model, whose space-time complexity increases linearly with the number of basic components in the circuit. In addition, it is found that the sensitivity of the input vector increases with the increase of fault probability of the basic components of the circuit. The influence of electric shielding effect and latch window shielding effect on the sensitivity of input vector is also increasing with the increase of fault probability of the basic components of the circuit, especially the electric shielding effect.
【作者单位】： 浙江工业大学计算机科学与技术学院 同济大学软件学院
【基金】：国家自然科学基金(61502422,61432017,61374152,61773348,61374094) 浙江省自然科学基金(LY18F020028,LQ15F020006,LY17F030016,Y18F030084)资助~~
【分类号】：TP331
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，本文编号：2331862
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