摘要
电路集成度和复杂度的不断增加使电路故障诊断变得愈加困难 .其中 ,测试集优化问题是电路故障诊断的关键问题之一 .本文以新颖的蚁群算法为基础 ,较好地解决了测试集的优化问题 ,并通过实验证明了该算法的良好性能 .
The increase of digital circuit integrity and complexity has made fault diagnosis of circuits more and more difficult.The scale of test set has become very large because of redundancy,which costs lots of time and memory unnecessarily.It is important to acquire optimal test set for test application.Test set optimization,which can eliminate the redundancy,is one of key problems in fault diagnosis of digital circuits.Ant colony optimization,a new kind of random optimization algorithm,has become a better alternative to genetic algorithm in some areas.That algorithm has such advantages as less parameters and simple operations,so it is easier to be adopted.We propose a method based on ant colony optimization that solves test set optimization better than classic algorithm or genetic algorithm.The better performance of the proposed method is demonstrated by experimental results.
出处
《电子学报》
EI
CAS
CSCD
北大核心
2003年第8期1178-1181,共4页
Acta Electronica Sinica
关键词
蚁群算法
测试集优化
故障诊断
ant algorithm
test optimization
fault diagnosis
