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Genetic algorithm based test pattern generation for multiple stuck-at faults and test power reduction in VLSI circuits

机译:基于遗传算法基于VLSI电路的多卡故障的测试模式生成和测试功率降低

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A method of test pattern generation for multiple stuck-at faults in VLSI circuits, using genetic algorithm is proposed. The test patterns were earlier generated for single stuck at faults only but in the proposed work, multiple faults are considered and fault masking is also taken into account when faults are injected. The test patterns to detect the faults are the binary values given as inputs to the circuit under test. These patterns should be compact and also should have minimum switching among them to reduce the test power. Genetic Algorithms (GA) is a search technique to find solutions to optimization and search problems. Hence the proposed work uses GA to generate test patterns. Here the chromosomes in GA are substituted for the test patterns. The test patterns are initialized randomly and their fitness value is evaluated. Now GA operators like selection, crossover and mutation are applied on this initial set to reproduce better test patterns. These generated test patterns are reordered using reordering techniques, don't cares filled by filling techniques to reduce the switching activity among them thus reducing the test power.
机译:提出了一种使用遗传算法的VLSI电路中多卡在VLSI电路故障的测试模式生成方法。测试模式早期为单次陷入困境,仅在拟议的工作中生成,但在提出的工作中,考虑了多个故障并在注入故障时考虑故障屏蔽。检测故障的测试模式是作为被测电路的输入给出的二进制值。这些图案应该是紧凑的,并且在其中也应该有最小的切换,以降低测试功率。遗传算法(GA)是寻找优化和搜索问题的解决方案的搜索技术。因此,所提出的工作使用GA生成测试模式。这里,Ga中的染色体被取代用于测试模式。试验模式随机初始化,评估其适应值。现在,在这个初始集合上应用了选择,交叉和突变的GA运算符以重现更好的测试模式。这些生成的测试模式使用重新排序技术重新排序,不要通过填充技术来填充以减少它们之间的切换活动,从而降低了测试功率。

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