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Solving Hard Local Minima Problems Using Basin Cells for Multilayer Perceptron Training

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Advances in Neural Networks – ISNN 2005 (ISNN 2005)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 3496))

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Abstract

An analysis of basin cells for an error surface of an multilayer perceptron is presented. Utilizing the topological structure of the basin cells, an escaping strategy is proposed to solve difficult local minima problems. A numerical example is given to illustrate the proposed method and is shown to have a potential to locate better local minima efficiently.

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Author information

Authors and Affiliations

  1. Department of Physics, Chung-Ang University, Seoul, 156-756, Korea

    Younggui Yoon

  2. Department of Industrial and Management Engineering, Pohang University of Science and Technology, Pohang, Kyungbuk, 790-784, Korea

    Jaewook Lee

Authors
  1. Younggui Yoon
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  2. Jaewook Lee
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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. The Key Laboratory of Optoelectric Technology & Systems, Ministry of Education, China

    Xiaofeng Liao

  3. Computational Intelligence Laboratory, School of Computer Science and Engineering, University of Electronic Science and Technology of China, 610054, Chengdu, P.R. China

    Zhang Yi

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© 2005 Springer-Verlag Berlin Heidelberg

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Yoon, Y., Lee, J. (2005). Solving Hard Local Minima Problems Using Basin Cells for Multilayer Perceptron Training. In: Wang, J., Liao, X., Yi, Z. (eds) Advances in Neural Networks – ISNN 2005. ISNN 2005. Lecture Notes in Computer Science, vol 3496. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11427391_95

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  • DOI: https://doi.org/10.1007/11427391_95

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-25912-1

  • Online ISBN: 978-3-540-32065-4

  • eBook Packages: Computer ScienceComputer Science (R0)

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