Characterisation of Analogue Macromodels under Fault Conditions using a Probabilistic Neural Network
نویسنده
چکیده
A technique for parameterising the macromodels of analogue circuit blocks under fault conditions is described. The technique uses a Robust Heteroscedastic Probabilistic Neural Network to classify simulation data. A large reduction in the number of fault classes can be obtained. The classification process is fast and the macromodels generated are accurate.
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