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Experimental Study of Elman Network in Temporal Classification

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Emerging Trends in Neuro Engineering and Neural Computation

Part of the book series: Series in BioEngineering ((SERBIOENG))

Abstract

Elman network is an extension of multilayer perceptron (MLP), where it introduces single hidden layer architecture, as well as an additional state table to store the time units for hidden neurons. This additional state table allows it to do the sequential prediction which is not possible in MLP. To examine its general performance as a temporal classifier, a Weka version of Elman network is exploited on 11 public temporal datasets released by UCI Machine Repository.

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Author information

Authors and Affiliations

  1. Faculty of Information Science and Technology, Multimedia University, Jalan Ayer Keroh Lama, 75450, Melaka, Malaysia

    Shih Yin Ooi, Shing Chiang Tan & Wooi Ping Cheah

Authors
  1. Shih Yin Ooi
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  2. Shing Chiang Tan
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  3. Wooi Ping Cheah
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Corresponding author

Correspondence to Shih Yin Ooi .

Editor information

Editors and Affiliations

  1. Geelong Waurn Ponds Campus, Deakin University, Institute for Intelligent Systems Research and Innovation, 3216 Waurn Ponds, Victoria, Australia

    Asim Bhatti

  2. Mayo Clinic, 55905 Rochester, Minnesota, USA

    Kendall H. Lee

  3. Materials Science and Engineering, Georgia Institute of Technology, 30332-0245 Atlanta, Georgia, USA

    Hamid Garmestani

  4. Geelong Waurn Ponds Campus, Deakin University, Institute for Intelligent Systems Research and Innovation, 3216 Waurn Ponds, Victoria, Australia

    Chee Peng Lim

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© 2017 Springer Nature Singapore Pte Ltd.

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Ooi, S.Y., Tan, S.C., Cheah, W.P. (2017). Experimental Study of Elman Network in Temporal Classification. In: Bhatti, A., Lee, K., Garmestani, H., Lim, C. (eds) Emerging Trends in Neuro Engineering and Neural Computation. Series in BioEngineering. Springer, Singapore. https://doi.org/10.1007/978-981-10-3957-7_14

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  • DOI: https://doi.org/10.1007/978-981-10-3957-7_14

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  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-10-3955-3

  • Online ISBN: 978-981-10-3957-7

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