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Correntropy-Induced Metric-Based Variable Step Size Normalized Least Mean Square Algorithm in Sparse System Identification

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First International Conference on Sustainable Technologies for Computational Intelligence

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 1045))

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Abstract

This paper incorporates a correntropy-induced metric (CIM)-based sparsity constraint into variable step size normalized least mean square (VSSNLMS) algorithm for identification of sparse system corrupted by additive noise. The proposed CIM-VSSNLMS algorithm makes a good trade-off between convergence characteristics, filter stability, and steady state error. The proposed (CIM-VSSNLMS) algorithm incorporates a variable step size that accelerates the convergence characteristics and lowers the normalized misalignment (NMSA) error with respect to CIM-NLMS with constant value of step size. An expression for variant step size is derived under the stability condition of proposed algorithm. Finally, the implementation of the proposed algorithm is carried out in MATLAB software to manifest the improved estimated behavior in the identification of sparse system.

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Author information

Authors and Affiliations

  1. Maharaja Agrasen Institute of Technology, Guru Gobind Singh Indraprastha University, New Delhi, Delhi, 110078, India

    Rajni Yadav & Sonia Jain

  2. University School of Information, Communication and Technology, Guru Gobind Singh Indraprastha University, New Delhi, Delhi, 110078, India

    C. S. Rai

Authors
  1. Rajni Yadav
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  2. Sonia Jain
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  3. C. S. Rai
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Corresponding author

Correspondence to Rajni Yadav .

Editor information

Editors and Affiliations

  1. Department of Electrical and Communication Engineering, The Papua New Guinea University of Technology, Lae, Papua New Guinea

    Ashish Kumar Luhach

  2. Neumann János University, Kecskemét, Bács-Kiskun, Hungary

    Janos Arpad Kosa

  3. Amity University, Jaipur, Rajasthan, India

    Ramesh Chandra Poonia

  4. School of Computing, University of Eastern Finland, Kuopio, Finland

    Xiao-Zhi Gao

  5. Department of Computer Science, Namibia University of Science and Technology, Windhoek, Namibia

    Dharm Singh

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Yadav, R., Jain, S., Rai, C.S. (2020). Correntropy-Induced Metric-Based Variable Step Size Normalized Least Mean Square Algorithm in Sparse System Identification. In: Luhach, A., Kosa, J., Poonia, R., Gao, XZ., Singh, D. (eds) First International Conference on Sustainable Technologies for Computational Intelligence. Advances in Intelligent Systems and Computing, vol 1045. Springer, Singapore. https://doi.org/10.1007/978-981-15-0029-9_47

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