Abstract: In order to improve fault diagnosis rate of analog circuits and solve the problem of analog circuit complexity, a new innovative fault diagnosis method which combined Least Squares Support Vector Machine（LSSVM） with Hidden Markov Model（HMM） is proposed. Firstly, the features of circuit fault are extracted, and then HMM and LSSVM are combined to build fault diagnosis model of analog circuits, and finally the simulation experiments are carried out to test the performance of mole. The results show that compared with other models, the proposed model has improved fault diagnosis rate and fastened the speed of fault diagnosis of analog circuits.

Key words: analog circuit, fault diagnosis, Hidden Markov Model（HMM）, Least Squares Support Vector Machine（LSSVM）

摘要： 为了提高模拟电路故障诊断正确率，针对单一模型难以获得高正确率检测结果的难题，基于组合优化理论，提出一种隐马尔科夫和最小二乘支持向量机的模拟电路故障诊断模型。提取电路故障特征，然后利用隐马尔科夫模型和最小二乘支持向量机建立模拟电路故障组合诊断模型，最后采用仿真实验对组合模型的性能进行分析。结果表明，相对于其他模拟电路故障诊断模型，该模型不仅提高了模拟电路故障检测正确率，而且具有更快的故障诊断速度。

关键词: 模拟电路, 故障诊断, 隐马尔科夫模型, 最小二乘支持向量机