Abstract
A new method of analog IC fault diagnosis is proposed in this paper, which is based on wavelet neural network ensemble (WNNE) technique and Adaboost algorithm. 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 fault diagnosis of a radar scanning circuit is implemented with this new method. The simulation results show that the new method is more effective than the traditional wavelet neural network (WNN) method.
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© 2009 Springer-Verlag Berlin Heidelberg
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Zuo, L., Hou, L., Wu, W., Wang, J., Geng, S. (2009). Fault Diagnosis of Analog IC Based on Wavelet Neural Network Ensemble. In: Yu, W., He, H., Zhang, N. (eds) Advances in Neural Networks – ISNN 2009. ISNN 2009. Lecture Notes in Computer Science, vol 5553. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-01513-7_84
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DOI: https://doi.org/10.1007/978-3-642-01513-7_84
Publisher Name: Springer, Berlin, Heidelberg
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