Comments on "Constructive learning of recurrent neuralnetworks: limitations of recurrent cascade correlation and a simplesolution"


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Comments by Javier Solana on 13 May 2008

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      Views: (2003)   Date: (Publication Date: Jul 1996)   Pages: ()
    • Author:  Kremer  S.C. Communication Res. Centre  Ottawa  Ont.;  

    • Abstract:  Abstract Giles et al. (1995) have proven that Fahlman's recurrent cascade correlation (RCC) architecture is not capable of realizing finite state automata that have state-cycles of length more than two under a constant input signal. This paper extends the conclusions of Giles et al. by showing that there exists a corollary to their original proof which identifies a large second class of automata, that is also unrepresentable by RCC

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