Introduction to statistical pattern recognition (2nd ed.)
Introduction to statistical pattern recognition (2nd ed.)
Ten lectures on wavelets
A translation-invariant wavelet representation algorithm withapplications
IEEE Transactions on Signal Processing
De-noising by soft-thresholding
IEEE Transactions on Information Theory
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The principal component analysis (PCA) is a popular projection method in neural spike sorting. When the waveforms extracted from a spike train are aligned incorrectly, however, the projection performance of the PCA deteriorates drastically, and the clustering errors multiply. This drawback is taken care of by the frequency domain PCA in this paper. By experiments, it is shown that the proposed approach maintains good projection performance under considerable alignment errors of the waveforms.