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.
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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.
Zhang Bo, Zhang Linget al., The Complexity of Learning Algorithm in PLN Network. International Joint Conference on Neural Network (IJCNN'91), Singapore, Nov. 1991.
I. Aleksander (eds.), Neural Computing Architectures. MIT Press, 1989.
J. Stephen Judd, Neural Network Design and the Complexity of Learning. MIT Press, 1990.
J. G. Kemey and J. L. Snell. Finite Markov Chains. Springer-Verlag, 1976.
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Zhang, B., Zhang, L. The complexity of recognition in the single-layered PLN network with feedback connections. J. of Compt. Sci. & Technol. 8, 317–321 (1993). https://doi.org/10.1007/BF02939538
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DOI: https://doi.org/10.1007/BF02939538