基于小波概率神经网络的CMOS电路IDDT诊断方法  

IDDT Diagnosis Method of CMOS Circuit Based on Wavelet Probabilistic Neural Network

作　　者：熊波[1] 潘强[1] 

机构地区：[1]海军工程大学电子工程学院,武汉430033

出　　处：《舰船电子工程》2016年第3期112-114,142,共4页Ship Electronic Engineering

摘　　要：近年来利用动态电流(IDDT)测试研究CMOS电路故障的方法得到广泛关注。论文结合小波变换和概率神经网络方法,提出一种基于小波分析和神经网络的IDDT诊断方法。小波分析具有时频局部化特征,能有效提取突变信号特征,概率神经网络训练容易,收敛速度快,可以实现任意的非线性逼近,具有良好的分类效果。论文结合二者优点,实现对CMOS电路故障的诊断,达到90%以上准确率。In recent years ,IDDT is widely used in studying the fault of CMOS circuit .Combined with wavelet trans-form and probabilistic neural network ,an IDDT diagnosis method based on wavelet analysis and neural network is proposed . With the characteristic of time and frequency localization ,wavelet analysis can effectively extract the characteristic of muta-tion signal ,and makes probabilistic neural network training easier ,possesses fast convergence speed and good classification results ,and can realize any nonlinear approximation .Combine with the advantages of wavelet transform and neural network , the fault diagnosis of CMOS circuit is realized with more than 90% accuracy .

关 键 词：小波分析 概率神经网络 CMOS 电路 

分 类 号：TP391[自动化与计算机技术—计算机应用技术]