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Fault diagnosis based on deep learning by extracting inherent common feature of multi-source heterogeneous data.

, , , , and . J. Syst. Control. Eng., (2021)

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A Cross Working Condition Multiscale Recursive Feature Fusion Method for Fault Diagnosis of Rolling Bearing in Multiple Working Conditions., , and . IEEE Access, (2022)Hybrid DCA-PCA Multiple Faults Diagnosis Method., , and . ICINCO-ICSO, page 367-370. INSTICC Press, (2009)Federated Learning Based Fault Diagnosis Driven by Intra-Client Imbalance Degree., , , and . Entropy, 25 (4): 606 (April 2023)A personalized federated learning-based fault diagnosis method for data suffering from network attacks., , , , , and . Appl. Intell., 53 (19): 22834-22849 (October 2023)An active federated method driven by inter-client informativeness variability of labeled data., , , , and . Signal Image Video Process., 17 (8): 3973-3982 (November 2023)A sparse denoising deep neural network for improving fault diagnosis performance., , , , and . Signal Image Video Process., 15 (8): 1889-1898 (2021)Inverse projection group sparse representation for tumor classification: A low rank variation dictionary approach., , , , , and . Knowl. Based Syst., (2020)Real-time fault diagnosis using deep fusion of features extracted by parallel long short-term memory with peephole and convolutional neural network., , and . J. Syst. Control. Eng., (2021)Deep learning fault diagnosis method based on global optimization GAN for unbalanced data., , , , and . Knowl. Based Syst., (2020)A Multiscale Recursive Attention Gate Federation Method for Multiple Working Conditions Fault Diagnosis., , , , , and . Entropy, 25 (8): 1165 (August 2023)