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Research of Blind Deconvolution Algorithm Based on High-Order Statistics and Quantum Inspired GA

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Advances in Natural Computation (ICNC 2005)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 3611))

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Abstract

This paper analyzes the network structure and algorithm model of Multi-Input and Multi-Output (MIMO) blind deconvolution, proposes a novel blind deconvolution algorithm based on output signals’ context information, and puts forward a new optimum method using Quantum Inspired Genetic Algorithm (QIGA). The simulation results demonstrate the effectiveness of the algorithm to the separation of communication signals.

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Author information

Authors and Affiliations

  1. 702 Research Division of Electronic Engineering Institute, Hefei, 230037, China

    Jun-an Yang & Bin Zhao

  2. Depart. of Electronic Engineering and Information Science of USTC, Hefei, 230036, China

    Jun-an Yang & Zhongfu Ye

Authors
  1. Jun-an Yang
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  2. Bin Zhao
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  3. Zhongfu Ye
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Editor information

Editors and Affiliations

  1. School of Electrical and Electronic Engineering, Nanyang Technological University, Block S1, Nanyang Avenue, 639798, Singapore

    Lipo Wang

  2. School of Software, Sun Yat-Sen University, 510275, Guangzhou, China

    Ke Chen

  3. School of Computer Engineering, Nanyang Technological University, BLK N4, 2b-39, Nanyang Avenue, 639798, Singapore

    Yew Soon Ong

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© 2005 Springer-Verlag Berlin Heidelberg

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Yang, Ja., Zhao, B., Ye, Z. (2005). Research of Blind Deconvolution Algorithm Based on High-Order Statistics and Quantum Inspired GA. In: Wang, L., Chen, K., Ong, Y.S. (eds) Advances in Natural Computation. ICNC 2005. Lecture Notes in Computer Science, vol 3611. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11539117_67

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  • DOI: https://doi.org/10.1007/11539117_67

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-28325-6

  • Online ISBN: 978-3-540-31858-3

  • eBook Packages: Computer ScienceComputer Science (R0)

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