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基于粒子群算法的故障测试集优化 被引量:9

Fault Test Set Optimization Based on Particle Swarm Optimization Algorithm
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摘要 为加速测试进程和减少测试开销,数字集成电路在生成测试矢量后必须进行故障测试集的优化。文中利用粒子群优化算法生成最小完备测试集,根据故障测试集优化问题的具体特点,构造粒子的表达方式和编码规则,建立粒子群的速度—位置模型;同时为提高优化效率,引入混沌优化算法来初始化粒子群。实验结果表明,在测试生成后,该方法能在较短的时间内生成最小完备测试集,验证了它的实用性和有效性。 To accelerate test generating test vectors for digital process and cut down the test spending, the fault test set must be optimized alter integrated circuits. This paper presents an algorithm to generate the minimum complete test set using particle swarm optimization (PSO). According to the actual characteristics of fault test set optimization, the particle expression and coding rule are constructed, and the speed -position model of PSO is established for fault test set optimization of digital integrated circuits. At the same time, in order to improve the optimization efficiency chaos optimization algorithm is introduced to initialize the particle population. Experimental results show that this method can generate the minimum complete test set in shorter time after test generation, which proves the effectiveness and applicability of the proposed algorithm.
出处 《电子测量与仪器学报》 CSCD 2008年第4期21-25,共5页 Journal of Electronic Measurement and Instrumentation
关键词 测试集优化 粒子群算法 混沌优化 测试生成 test set optimization, PSO algorithm, chaos optimization, test generation.
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参考文献7

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