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A New Kalman Filtering Algorithm for Nonlinear Principal Component Analysis

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Advances in Neural Networks – ISNN 2005 (ISNN 2005)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 3496))

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Abstract

This paper addresses the problem of blind source separation (BSS) based on nonlinear principal component analysis (NPCA), and presents a new Kalman filtering algorithm, which applies a different state-space representation from the one proposed recently by Lv et al. It is shown that the new Kalman filtering algorithm can be simplified greatly under certain conditions, and it includes the existing Kalman-type NPCA algorithm as a special case. Comparisons are made with several related algorithms and computer simulations on BSS are reported to demonstrate the validity.

This work was supported by the major program of the National Natural Science Foundation of China (No. 60496311), by the Chinese Postdoctoral Science Foundation (No. 2004035061), and by the Foundation of Intel China Research Center.

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Author information

Authors and Affiliations

  1. Department of Automation, Tsinghua University, Beijing, 100084, China

    Xiaolong Zhu & Xianda Zhang

  2. Intel China Research Center, Beijing, 100080, China

    Ying Jia

Authors
  1. Xiaolong Zhu
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  2. Xianda Zhang
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  3. Ying Jia
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Editor information

Editors and Affiliations

  1. Department of Mechanical and Automation Engineering, The Chinese University of Hong Kong, Shatin, New Territories, Hong Kong, China

    Jun Wang

  2. The Key Laboratory of Optoelectric Technology & Systems, Ministry of Education, China

    Xiaofeng Liao

  3. Computational Intelligence Laboratory, School of Computer Science and Engineering, University of Electronic Science and Technology of China, 610054, Chengdu, P.R. China

    Zhang Yi

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© 2005 Springer-Verlag Berlin Heidelberg

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Zhu, X., Zhang, X., Jia, Y. (2005). A New Kalman Filtering Algorithm for Nonlinear Principal Component Analysis. In: Wang, J., Liao, X., Yi, Z. (eds) Advances in Neural Networks – ISNN 2005. ISNN 2005. Lecture Notes in Computer Science, vol 3496. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11427391_162

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  • DOI: https://doi.org/10.1007/11427391_162

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-25912-1

  • Online ISBN: 978-3-540-32065-4

  • eBook Packages: Computer ScienceComputer Science (R0)

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