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基于粒子群算法的电路测试集优化 被引量：1

Test set optimization based on particle swarm optimization for circuits
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摘要 研究电路测试集的优化，提出基于粒子群算法的电路测试集的静态压缩方法．粒子群向最优解方向演绎，利用适应度函数来评价各粒子的优劣．实验电路的验证结果表明，同时适用于时序电路和组合电路，与基于遗传算法的电路测试集优化相比，该算法能够更大限度地优化测试集，需要更少的存储空间． The paper researches on test set optimization for circuits, and proposes a new static compaction method based on particle swarm optimization. The PSO evolves candidate test pattern, using fitness function to evaluate every particle. Experimental results derived from some experimental circuits illustrate that the method is applicable for both sequential circuits and combinational circuits. Compared with GA-based test set optimization, this proposed algorithm can compact test set to much more extent and require much less storage space.
作者 侯艳丽 赵春晖 廖艳苹
机构地区 哈尔滨工程大学信息与通信工程学院
出处 《哈尔滨工程大学学报》 EI CAS CSCD 北大核心 2006年第B07期506-509,共4页 Journal of Harbin Engineering University
关键词 测试集优化 粒子群算法 时序电路 组合电路 test set optimization particle swarm optimization sequential circuits combinational circuits
分类号 TN929 [电子电信—通信与信息系统]
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参考文献8

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同被引文献12

  • 1康波,陈光■,吕炳朝.基于混沌遗传算法的故障测试集最小化方法[J].仪器仪表学报,2005,26(1):100-103. 被引量：8
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  • 6HAMZAOGLU I, PATEL J H. Test set compaction algorithms for combinational circuits [ J ]. IEEE Trans. Compurer- Aided Design Integr. Circuits Syst, 2000,19(8): 957-963.
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  • 8FLORES P F, NETO H C, MARQUES-SILVA J P. On applying set covering models to test set compaction [ A ]. In Proceeding of the 9^th Great Lakes Symposium on VLSI [ C ]. Los Alamitos: IEEE Computer Society Press, 1999:8-11.
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哈尔滨工程大学学报
2006年 第B07期

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