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Journal of Computer Science and Technology

, Volume 8, Issue 4, pp 317–321 | Cite as

The complexity of recognition in the single-layered PLN network with feedback connections

  • Bo Zhang
  • Ling Zhang
Regular Papers
  • 15 Downloads

Abstract

Regarding a single-layered PLN network with feedback connections as an associative memory network, the complexity of recognition is discussed. We have the main result: if the size of the networkN ism, then the complexity of recognition is an exponential function ofm. The necessary condition under which the complexity of recognition is polynomial is given.

Keywords

PLN network stable state associative memory network Markov chain transition matrix complexity of recognition 

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References

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    Zhang Bo, Zhang Ling,et al., The quantitative analysis of the behaviors of the PLN network.Neural Networks, 1992, 5(4), pp. 639–644.CrossRefGoogle Scholar
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    Zhang Bo, Zhang Linget al., The Complexity of Learning Algorithm in PLN Network. International Joint Conference on Neural Network (IJCNN'91), Singapore, Nov. 1991.Google Scholar
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    I. Aleksander (eds.), Neural Computing Architectures. MIT Press, 1989.Google Scholar
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    J. Stephen Judd, Neural Network Design and the Complexity of Learning. MIT Press, 1990.Google Scholar
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    J. G. Kemey and J. L. Snell. Finite Markov Chains. Springer-Verlag, 1976.Google Scholar

Copyright information

© Science Press, Beijing China and Allerton Press Inc. 1993

Authors and Affiliations

  • Bo Zhang
    • 1
  • Ling Zhang
    • 2
  1. 1.Dept. of Computer Science and TechnologyTsinghua UniversityBeijing
  2. 2.Dept. of MathematicsAnqing Teachers' CollegeAnqing, Anhui

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