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An Efficient Memory-Improved Proportionate Affine Projection Sign Algorithm Based on l 0-Norm for Sparse System Identification

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Foundations of Intelligent Systems

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 277))

Abstract

An efficient MIP-APSA (EMIP-APSA) is proposed via incorporating l 0-norm as a better measure of sparseness into a recently presented memory-improved proportionate affine projection sign algorithm (MIP-APSA) to enhance performance for sparse system identification. Also, to reduce computational complexity of EMIP-APSA, we achieve a simple implementation of the EMIP-APSA (SEMIP-APSA) while maintaining the consistent performance in terms of convergence rate and steady-state misalignment. Simulation results demonstrate that the proposed EMIP-APSA and SEMIP-APSA obtain a lower steady-state misalignment in comparison with the MIP-APSA for sparse system identification in the impulsive noise environment.

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Acknowledgment

This work was partially supported by National Science Foundation of P. R. China (Grant: 61271340 and 61071183), the State 863 projects (Grant: 2011AA110501), the Sichuan Provincial Youth Science and Technology Fund (Grant: 2012JQ0046), and the Fundamental Research Funds for the Central Universities (Grant: SWJTU12CX026).

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Authors and Affiliations

  1. School of Electrical Engineering, Southwest Jiaotong University, Chengdu, China

    Yi Yu & Haiquan Zhao

Authors
  1. Yi Yu
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  2. Haiquan Zhao
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Corresponding author

Correspondence to Yi Yu .

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Editors and Affiliations

  1. College of Computer and Software Engineering, Shenzhen University, Shenzhen, China

    Zhenkun Wen

  2. School of Information Science and Technology, Southwest Jiaotong University, Chengdu, China

    Tianrui Li

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Yu, Y., Zhao, H. (2014). An Efficient Memory-Improved Proportionate Affine Projection Sign Algorithm Based on l 0-Norm for Sparse System Identification. In: Wen, Z., Li, T. (eds) Foundations of Intelligent Systems. Advances in Intelligent Systems and Computing, vol 277. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-54924-3_48

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  • DOI: https://doi.org/10.1007/978-3-642-54924-3_48

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  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-54923-6

  • Online ISBN: 978-3-642-54924-3

  • eBook Packages: EngineeringEngineering (R0)

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