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Solution Space of Perceptron

  • Conference paper
Artificial Neural Networks – ICANN 2010 (ICANN 2010)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 6354))

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Abstract

Any point in the solution space of a perceptron can classify the training data correctly. Two kinds of the solution space, one in the weight space and the other in the input space, have been devised. This work illustrated the correspondence between these two spaces.

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References

  1. McCulloch, W.S., Pitts, W.: A Logical Calculus on the Ideas Immanent in the Nervous Activity. Bull. Math. Biophys. 5, 115–133 (1943)

    Article  MATH  MathSciNet  Google Scholar 

  2. Minsky, M., Papert, S.: Perceptrons. MIT Press, Cambridge (1969)

    MATH  Google Scholar 

  3. Liou, C.-Y., Chen, H.-T.: Self-Relaxation for Multilayer Perceptron. In: The Third Asian Fuzzy Systems AFSS 1998, Masan, Korea, June 18-21, pp. 113–117 (1998)

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  4. Liou, C.-Y., Huang, J.-C., Kuo, Y.-T.: Geometrical Perspective on Learning Behavior. Journal of Information Science and Engineering 21, 721–732 (2005)

    MathSciNet  Google Scholar 

  5. Diamantaras, K.I., Strintzis, M.G.: Neural Classifiers Using One-Time Updating. IEEE Trans. Neural Networks 9(3), 436–447 (1998)

    Article  Google Scholar 

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Author information

Authors and Affiliations

  1. Department of Computer Science and Information Engineering, National Taiwan University, Taiwan, Republic of China

    Jau-Chi Huang & Cheng-Yuan Liou

Authors
  1. Jau-Chi Huang
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  2. Cheng-Yuan Liou
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Editor information

Editors and Affiliations

  1. Department of Informatics, TEI of Thessaloniki, 57400, Sindos, Greece

    Konstantinos Diamantaras

  2. Department of Informatics, Nicolaus Copernicus University, School of Physics, Astronomy, and Informatics, ul. Grudziadzka 5, 87-100, Torun, Poland

    Wlodek Duch

  3. Department of Forestry and Management of the Environment and Natural Resources, Democritus University of Thrace, Pantazidou 193, 68200, Orestiada Thrace, Greece

    Lazaros S. Iliadis

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© 2010 Springer-Verlag Berlin Heidelberg

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Huang, JC., Liou, CY. (2010). Solution Space of Perceptron. In: Diamantaras, K., Duch, W., Iliadis, L.S. (eds) Artificial Neural Networks – ICANN 2010. ICANN 2010. Lecture Notes in Computer Science, vol 6354. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-15825-4_34

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  • DOI: https://doi.org/10.1007/978-3-642-15825-4_34

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-15824-7

  • Online ISBN: 978-3-642-15825-4

  • eBook Packages: Computer ScienceComputer Science (R0)

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