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Blind Identification and Deconvolution for Noisy Two-Input Two-Output Channels

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Advances in Neural Networks – ISNN 2005 (ISNN 2005)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 3497))

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Abstract

This paper discusses blind identification and deconvolution of two-input two-output channels corrupted by noises based on second-order statistics. First, the identifiability of channel is analyzed. By constructing an new criterion, the channel parameters can be identified precisely in the present of noises. Second, the cost function of identification is established and the corresponding algorithm is presented. Next, a feedback model is used for deconvolution, and several important problems, such as the effect of noises in the blind deconvolution of mixed sources and the stability of deconvolution model, are discussed. At last, simulation results are given to illustrate the theoretical results of this paper.

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Author information

Authors and Affiliations

  1. Institute for Infocomm Research, Singapore, 119613

    Yuanqing Li

  2. Laboratory for Advanced Brain Signal Processing, RIKEN Brain Science Institute, Wako Shi, Saitama, 3510198, Japan

    Andrzej Cichocki

  3. Institute of Automation Science and Engineering, South China University of Technology, Guangzhou, 510641, China

    Jianzhao Qin

Authors
  1. Yuanqing Li
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  2. Andrzej Cichocki
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  3. Jianzhao Qin
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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

    Xiao-Feng 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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Li, Y., Cichocki, A., Qin, J. (2005). Blind Identification and Deconvolution for Noisy Two-Input Two-Output Channels. In: Wang, J., Liao, XF., Yi, Z. (eds) Advances in Neural Networks – ISNN 2005. ISNN 2005. Lecture Notes in Computer Science, vol 3497. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11427445_82

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  • DOI: https://doi.org/10.1007/11427445_82

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-25913-8

  • Online ISBN: 978-3-540-32067-8

  • eBook Packages: Computer ScienceComputer Science (R0)

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