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Fault redundancy information can increase computation complexity and reduce the precision of fault diagnosis. Feature extraction becomes very important to improve the performance of fault diagnosis. A supervised kernel learning algorithm based on manifold is presented to carry out feature extraction. The proposed algorithm firstly implements locality preserving projection in reproducing kernel Hilbert...
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