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Action Potential Classification Based on LVQ Neural Network

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Rough Set and Knowledge Technology (RSKT 2010)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 6401))

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Abstract

Neural action potential classification is the prerequisite condition of further neural information process, but there are difficulties in accurate action potential classification due to the existence of great amount of noise. In this paper, we propose a method of action potential classification based on Learning Vector Quantization (LVQ) network. In the experimental stage, the performance of the presented system was tested at various signal-to-noise ratio levels based on synthetic data. The results show that the proposed action potential classification method is effective. The proposed method supplies a new thought for action potential classification problem.

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References

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Author information

Authors and Affiliations

  1. School of Computer Science and Technology, Zhejiang University, Hangzhou, 310027, P.R. China

    Jian-Hua Dai, Qing Xu & Mianrui Chai

  2. Center for the Study of Language and Cognition, Zhejiang University, Hangzhou, 310028, P.R. China

    Jian-Hua Dai

  3. College of Medicine, Zhejiang University, Hangzhou, 310027, P.R. China

    Qida Hu

Authors
  1. Jian-Hua Dai
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  2. Qing Xu
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  3. Mianrui Chai
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  4. Qida Hu
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Editor information

Editors and Affiliations

  1. School of Computer and Information Technology, Beijing Jiaotong University, 100044, Beijing, China

    Jian Yu

  2. Faculty of Economics, University of Catania, Corso Italia, 55, 95129, Catania, Italy

    Salvatore Greco

  3. Department of Mathematics and Computing Science, Saint Mary’s University, B3H 3C3, Halifax, Nova Scotia, Canada

    Pawan Lingras

  4. Institute of Computer Science and Technology, Chongqing University of Posts and Telecommunications, 400065, Chongqing, China

    Guoyin Wang

  5. Institute of Mathematics, Warsaw University, Banacha 2, 02-097, Warsaw, Poland

    Andrzej Skowron

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© 2010 Springer-Verlag Berlin Heidelberg

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Dai, JH., Xu, Q., Chai, M., Hu, Q. (2010). Action Potential Classification Based on LVQ Neural Network. In: Yu, J., Greco, S., Lingras, P., Wang, G., Skowron, A. (eds) Rough Set and Knowledge Technology. RSKT 2010. Lecture Notes in Computer Science(), vol 6401. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-16248-0_65

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  • DOI: https://doi.org/10.1007/978-3-642-16248-0_65

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-16247-3

  • Online ISBN: 978-3-642-16248-0

  • eBook Packages: Computer ScienceComputer Science (R0)

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