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One fundamental problem with the kernel Fisher discriminant analysis (KFDA) for fault diagnosis, is the singularity problem of the within-class scatter matrix due to the small sample size. In this paper, a kernel scatter-difference-based discriminant analysis (KSDA) method is proposed for fault diagnosis. The proposed method can not only produce nonlinear discriminant features of the process data,...
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