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What is Neural Network Enabled Intermittent Fault Diagnosis Under Comparison Model about?

The document discusses a neural network-based algorithm, RNNIFDCom, for diagnosing intermittent faults in large-scale networks using partial syndromes under a comparison model. It highlights the challenges posed by intermittent faults, which can self-resolve and are unpredictable, and presents theoretical results that establish the diagnosability of general r-regular networks. The proposed algorithm

Author

yangrf17

Language

EN