Feature Extraction by Multi-Scale Principal Component Analysis and Classification in Spectral Domain


Feature extraction of signals plays an important role in classification problems because of data dimension reduction property and potential improvement of a classification accuracy rate. Principal component analysis (PCA), wavelets transform or Fourier transform methods are often used for feature extraction. In this paper, we propose a multi-scale PCA, which combines discrete wavelet transform, and PCA for feature extraction of signals in both the spatial and temporal domains. Our study shows that the multi-scale PCA combined with the proposed new classification methods leads to high classification accuracy for the considered signals.

Share and Cite:

Xie, S. , Lawnizak, A. , Lio, P. and Krishnan, S. (2013) Feature Extraction by Multi-Scale Principal Component Analysis and Classification in Spectral Domain. Engineering, 5, 268-271. doi: 10.4236/eng.2013.510B056.

Conflicts of Interest

The authors declare no conflicts of interest.


[1] I. T. Jolliffe, “Principal Component Analysis,” Springer Science+Bussiness Media, Inc., New York, 2004.
[2] M. S. Taqqu, V. Teverovsky and W. Willinger, “Is Network Traffic Self-Similar or Multifractal?” Fractals, Vol. 5, 1997, pp. 63-74. http://dx.doi.org/10.1142/S0218348X97000073
[3] B. Vidakovi, “Statistical Modeling by Wavelets,” John Wiley & Sons, Inc., Hoboken, 1999. http://dx.doi.org/10.1002/9780470317020
[4] D. Donoho, I. Johnstone, G. Kerkyacharian and D. Picard, “Wavelet Shrinkage: Asymptopia?” Journal of the Royal Statistical Society: Series B, Vol. 57, 1995, pp. 301-369.
[5] D. Donoho and I. Johnstone, “Minimax Estimation via Wavelet Shrinkage,” Annals of Statistics, Vol. 26, 1998, pp. 879-921. http://dx.doi.org/10.1214/aos/1024691081
[6] B. Bakshi, “Multiscale Analysis and Modeling Using Wavelets,” Journal of Chemometrics, Vol. 13, No. 3-4, 1999, pp. 415-434.
[7] R. G. Andrzejak, K. Lehnertz, F. Mormann, C. Rieke, P. David and C. E. Elger, “Indications of Nonlinear Deterministic and Finite-Dimensional Structures in Time Series of Brain Electrical Activity: Dependence on Recording Region and Brain State,” Physical Review E, Vol. 64, No. 6, 2001, p. 6190. http://dx.doi.org/10.1103/PhysRevE.64.061907

Copyright © 2023 by authors and Scientific Research Publishing Inc.

Creative Commons License

This work and the related PDF file are licensed under a Creative Commons Attribution 4.0 International License.