| 詹文法,余储贤,胡心怡,郑江云,张庆平,蔡雪原.D-PSO算法的单变量测试参数集成电路筛选方法[J].电子测量与仪器学报,2024,38(6):25-33 |
| D-PSO算法的单变量测试参数集成电路筛选方法 |
| One-variable test parameter integrated circuitscreening method for D-PSO algorithm |
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| DOI： |
| 中文关键词: 芯片筛选 K-means算法 D-PSO算法 拐点检测 |
| 英文关键词:chip screening K-means algorithm D-PSO algorithm inflection point detection |
| 基金项目:国家自然科学基金（61306046，61640421）、宜城精英项目（202371）、射频集成与微组装技术国家地方联合工程实验室开放课题（KFJJ20230101）、集成芯片与系统全国重点实验室项目资助 |
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| Author | Institution |
| Zhan Wenfa | School of Electronic Engineering and Intelligent Manufacturing, Anqing Normal University, Anqing
246133,China |
| Yu Chuxian | School of Computer and Information, Anqing Normal University, Anqing 246133,China |
| Hu Xinyi | School of Computer and Information, Anqing Normal University, Anqing 246133,China |
| Zheng Jiangyun | School of Electronic Engineering and Intelligent Manufacturing, Anqing Normal University, Anqing
246133,China |
| Zhang Qingping | School of Electronic Engineering and Intelligent Manufacturing, Anqing Normal University, Anqing
246133,China |
| Cai Xueyuan | School of Electronic Engineering and Intelligent Manufacturing, Anqing Normal University, Anqing
246133,China |
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| 中文摘要: |
| 针对集成电路尺寸缩小和复杂度提升导致的筛选成本提高问题，提出了一种针对单变量测试参数的集成电路筛选方法。具体先使用归并排序算法将参数值与集成电路编号拼接成数组，确保后续筛选的准确性，并按照参数值对数据进行排序。然后，利用K-means算法对测试数据的异常值进行预处理，对测试数据进行初步优化。最后，通过结合导数与粒子群优化算法创新性地提出了D-PSO算法，D-PSO算法增强了拐点位置定位的敏感性和准确性，能够精确地定位拐点，达到直接筛选出参数数据相近集成电路的目的。通过仿真实验的结果证明了该算法的收敛速度远高于其他算法，并能够准确、快速的筛选集成电路，在保持测试精度的同时，实现了测试集的优化和相似性筛选，有效降低了集成电路筛选成本。 |
| 英文摘要: |
| In response to the increased screening costs associated with the reduction in size and increased complexity of integrated circuits, a new screening method for integrated circuits based on single-variable test parameters has been proposed. Initially, the merge sort algorithm is used to concatenate the parameter values with the integrated circuit numbers into an array, ensuring the accuracy of subsequent screening and sorting the data according to parameter values. Then, the K-means algorithm is employed to preprocess outliers in the test data, optimizing the test data preliminarily. Finally, an innovative algorithm called D-PSO is introduced, combining derivatives and particle swarm optimization. The D-PSO algorithm enhances the sensitivity and accuracy of locating inflection points, precisely identifying these points to directly screen integrated circuits with similar parameter data. Simulation results demonstrate that this algorithm converges much faster than other algorithms and can accurately and swiftly screen integrated circuits. While maintaining test accuracy, it optimizes the test set and performs similarity screening, effectively reducing the screening costs of integrated circuits. |
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