LSSVM在指数寿命型小子样IC寿命预测的应用  

Application of LSSVM on Lifetime Prediction of IC with Small Sample from Exponential Distribution

作　　者：邹心遥[1] 姚若河[2] 

机构地区：[1]广东农工商职业技术学院电子与信息工程系,广州510507 [2]华南理工大学电子与信息学院,广州510640

出　　处：《科学技术与工程》2011年第24期5946-5949,共4页Science Technology and Engineering

基　　金：国家自然科学基金项目(60776020)资助

摘　　要：针对传统寿命预测方法需要大量样本与现代高可靠集成电路(IC)在寿命试验中通常只有少量失效样本的矛盾,提出了基于最小二乘支持向量机(LSSVM)的指数寿命型小子样IC寿命预测方法。用蒙特卡罗方法研究了该方法在指数寿命型IC寿命预测应用中的可行性。同时与基于神经网络的预测方法相比。结果表明基于LSSVM的方法能更精确地预测小子样下IC的寿命,可为预测指数寿命型小子样IC的寿命提供一种新的有效途径。It＇s becoming more and more difficult to get enough failure data sample during life test of modern integrated circuit（IC）.However traditional reliability assessment methods need a lot of failure data.In order to resolve this contradiction,a life prediction method of IC with small sample based on least squares support vector machine（LSSVM） is proposed.This method can be used to predict the lifetime of IC with small sample when the failure distributions are assumed to be exponential distribution.In addition,the effectiveness of LSSVM approach by Monte Carlo simulation is demonstrated.Error back propagation（BP） neural network is also compared with LSSVM method.The obtained results show that LSSVM method can be used to predict life of IC with small sample with high accuracy when dealing with failure data from exponential distribution.

关 键 词：寿命预测 最小二乘支持向量机 集成电路 小子样 指数分布 

分 类 号：TN47[电子电信—微电子学与固体电子学] TP202[自动化与计算机技术—检测技术与自动化装置]