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Hyper-Rectangle Model

  • Daniel S. YeungEmail author
  • Ian Cloete
  • Daming Shi
  • Wing W.Y. Ng
Chapter
Part of the Natural Computing Series book series (NCS)

Abstract

In this chapter, we discuss a hyper rectangle model, instead of the traditional hypersphere, which is employed as the mathematical model to represent an MLP’s input space. The hyper-rectangle approach does not demand that the input deviation be very small as the derivative approach requires, and the mathematical expectation used in the hyper-rectangle model reflects the network’s output deviation more directly and exactly than the variance does. Moreover, this approach is applicable to the MLP that deals with infinite input patterns, which is an advantage of the MLP over other discrete feedforward networks like Madalines.

Copyright information

© Springer-Verlag Berlin Heidelberg 2009

Authors and Affiliations

  • Daniel S. Yeung
    • 1
    Email author
  • Ian Cloete
    • 2
  • Daming Shi
    • 3
  • Wing W.Y. Ng
    • 1
  1. 1.School of Computer Science and Engineering, South China University of TechnologyGuangzhouChina
  2. 2.International University in GermanyBruchsalGermany
  3. 3.School of Electrical Engineering and Computer Science, Kyungpook National UniversityDaeguSouth Korea

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