Analog IC Fault Diagnosis based on Wavelet Neural Network Ensemble

Abstract

A fault diagnosis method for analog IC diagnosis based on wavelet neural network ensemble (WNNE) and Adaboost algorithm, is proposed in this paper. This makes the way of the directory be of use in fault, and enhances the validity of the fault diagnosis. Using wavelet decomposition as a tool for extracting feature, Then, after training the WNNE by faulty feature vectors, the model of the circuit with fault diagnosis system is built. Simulation results have shown that this claim is more effective than wavelet neural network (WNN).