| Autor: | Farzan Aminian, M. Aminian |
|---|---|
| Rok vydání: | 2001 |
| Předmět: |
Normalization (statistics)
Artificial neural network Analogue electronics Computer science business.industry Time delay neural network Wavelet transform Pattern recognition Hardware_PERFORMANCEANDRELIABILITY Bayesian inference Computer Science::Hardware Architecture Preprocessor Artificial intelligence Electrical and Electronic Engineering business Electronic circuit |
| Zdroj: | Journal of Electronic Testing. 17:29-36 |
| ISSN: | 0923-8174 |
| Popis: | We have developed an analog circuit fault diagnostic system based on Bayesian neural networks using wavelet transform, normalization and principal component analysis as preprocessors. Our proposed system uses these preprocessing techniques to extract optimal features from the output(s) of an analog circuit. These features are then used to train and test a neural network to identify faulty components using Bayesian learning of network weights. For sample circuits simulated using SPICE, our neural network can correctly classify faulty components with 96% accuracy. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
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