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Robust Recursive Complex Extreme Learning Machine Algorithm for Finite Numerical Precision

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Advances in Neural Networks - ISNN 2006 (ISNN 2006)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 3971))

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Abstract

Recently, a new learning algorithm for single-hidden-layer feedforward neural network (SLFN) named the complex extreme learning machine (C-ELM) has been proposed in [1]. In this paper, we propose a numerically robust recursive least square type C-ELM algorithm. The proposed algorithm improves the performance of C-ELM especially in finite numerical precision. The computer simulation results in the various precision cases show the proposed algorithm improves the numerical robustness of C-ELM.

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References

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Author information

Authors and Affiliations

  1. Dept. of Electronics Engineering, Sejong University, Kunja, Kwangjin, 98, 143-747, Seoul, Korea

    Junseok Lim

  2. School of Electrical Engineering, Seoul National University, Seoul, Korea

    Koeng Mo Sung

  3. Samsung Electronics Co., Ltd,  

    Joonil Song

Authors
  1. Junseok Lim
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  2. Koeng Mo Sung
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  3. Joonil Song
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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. Computational Intelligence Laboratory, School of Computer Science and Engineering, University of Electronic Science and Technology of China, 610054, Chengdu, P.R. China

    Zhang Yi

  3. Department of Electrical Engineering, University of Louisville, 40292, Louisville, KY, U.S.A

    Jacek M. Zurada

  4. Laboratory for Computational Biology, Shanghai Center for Systems Biomedicine, 800 Dong Chuan Rd., 200240, Shanghai, China

    Bao-Liang Lu

  5. School of Electrical and Electronic Engineering, University of Manchester, UK

    Hujun Yin

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© 2006 Springer-Verlag Berlin Heidelberg

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Lim, J., Sung, K.M., Song, J. (2006). Robust Recursive Complex Extreme Learning Machine Algorithm for Finite Numerical Precision. In: Wang, J., Yi, Z., Zurada, J.M., Lu, BL., Yin, H. (eds) Advances in Neural Networks - ISNN 2006. ISNN 2006. Lecture Notes in Computer Science, vol 3971. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11759966_94

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  • DOI: https://doi.org/10.1007/11759966_94

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-34439-1

  • Online ISBN: 978-3-540-34440-7

  • eBook Packages: Computer ScienceComputer Science (R0)

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