Description: Contains the eigenvalue and eigenvector extraction, the training sample, and the final recognition, Including the least squares method, the SVM, neural networks, 1 _k neighbor method, Verification is available, Is a good learning materials to learn PCA feature extraction, For lack of EMD, Weighted acceleration, The received signal is given eye and BER simulation systems.
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