Pseudo principal components analysis for feature extraction and pattern recognition of time-series data

  • D S An, K. W. Tang
  • Published 2004 in
    Proceedings of 2004 International Symposium on…

Abstract

We proposed a novel method to extract a feature from time-series data by principal components analysis (PCA) with time-delay embedding, and showed its usefulness in pattern recognition. We first resampled from the original time series data and constructed a new data with time-delay embedding. Then we applied PCA to the new data to get a pseudo principal… (More)

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