Multi-fault Diagnosis for Wide-deviation Analog Circuits Based on ELVQ Algorithm

In order to realize the multi-fault diagnosis for wide-deviation analog circuits, this paper designs a classification model based on Self-Organizing Map-Learning Vector Quantization(SOM-LVQ) network, and also presents an Enhanced LVQ (ELVQ) algorithm, in which the win-probability of neural can be balanced and the point density of the neural around the Bayesian decision surfaces can be reduced. The results of simulation indicate that the proposed algorithm has advantages of rapid convergence and low classification error.