Comments on "Constructive learning of recurrent neural networks: limitations of recurrent cascade correlation and a simple solution"
Stefan C. Kremer · IEEE Transactions on Neural Networks · 1996
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.