WEN Chenglin, ZHOU Funa, WEN Chuanbo, CHEN Zhiguo. An Extended Multi-scale Principal Component Analysis Method and Application in Anomaly Detection[J]. Chinese Journal of Electronics, 2012, 21(3): 471-476.
Citation: WEN Chenglin, ZHOU Funa, WEN Chuanbo, CHEN Zhiguo. An Extended Multi-scale Principal Component Analysis Method and Application in Anomaly Detection[J]. Chinese Journal of Electronics, 2012, 21(3): 471-476.

An Extended Multi-scale Principal Component Analysis Method and Application in Anomaly Detection

  • Received Date: 2011-04-01
  • Rev Recd Date: 2011-11-01
  • Publish Date: 2012-07-25
  • Multi-scale principal component analysis (MSPCA) can well implement multivariate information extracting on different scales, but theory foundation of MSPCA is still an open question. Using spectral decomposition of a matrix and multi-scale representation of spectral as well as multi-scale transform of a signal, an Extended multi-scale PCA (EMSPCA) method is proposed to analyze the reason why multi-scale detection method does well than single scale method. Under the uniform projection frame of EMSPCA, the relation between multi-scale detection model and those on each scale is established. Thus multi-scale anomaly detection can be implemented without establishing another new PCA model of the reconstructed data. Simulation shows the efficiency of EMSPCA anomaly detection algorithm.
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      沈阳化工大学材料科学与工程学院 沈阳 110142

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