Method and system of failure prediction
A fault prediction and fault direction technology, applied in electrical testing/monitoring, etc., can solve the problem that fault estimation technology cannot predict faults very accurately
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[0036] The present invention will be described in further detail below in conjunction with the accompanying drawings.
[0037] The Kernel Principal Component Analysis (KPCA) method is a new algorithm derived from the PCA method to study the nonlinear characteristics of data. The KPCA method is a nonlinear method based on the PCA method. It maps the input data x to a high-dimensional feature space F through a certain nonlinear mapping function φ( ), and then processes the data in F according to the linear principal component analysis method. . Transform the nonlinear problem in the original measurement space into a linear problem in the feature space.
[0038] assuming x 1 , x 2 ,...,x n ∈ R m are n m-dimensional column vector training samples for kernel principal component analysis learning. Let the nonlinear mapping be φ, the original data x i (i=1,2,...,n) in the mapping space F high The image in φ(x i ).
[0039] An n×n-dimensional kernel matrix K can be defined, ...
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