An application of an artificial neural network to reliability screen classification from noise measurement

Abstract

In this paper, we suggest that the reliability screen classification of BJTs from noise measurement belongs in statistical pattern recognition, then the multilayer artificial neural network is used as reliability screen classifier. The structure of a multilayer neural network (MLNN) with a back-propagation algorithm for training weights of the MLNN is discussed. This method can obtain optimal decision regions and the minimum summed squared error. Finally, an application of a neural network to the reliability screen classification of 100 BJTs is given, the results show that the MLNN is a feasible reliability screen classifier.