Bayesian Fault Diagnosis of RF Circuits Using Nonparametric Density Estimation

摘要：

This paper discusses a Bayesian fault diagnosis scheme for RF circuits. We use non-idealized spot defect models by taking into account both their resistive and capacitive behavior at the layout level. The likelihoods in the Bayes rule are estimated using nonparametric kernel density estimation. Our case study is an RF low noise amplifier. The diagnosis decisions and the subsequent defect ambiguity analysis are demonstrated using post-layout simulations.

作者: Ke Huang Haralampos-G. Stratigopoulos Salvador Mir

作者单位: TIMA Laboratory (CNRS-Grenoble INP-UJF), 46 Av. F61ix Viallet, 38031 Grenoble, France

会议类型: 国际会议

会议名称: 2010 19th IEEE Asian Test Symposium(第19届IEEE亚洲测试技术学术会议 ATS 2010)

会议地点: 上海

会议语种:英文

页码: 295-298

在线出版日期: 2010-12-01（万方平台首次上网日期，不代表论文的发表时间）