Discrete Recurrent Neural Networks
Part of the Network Theory and Applications book series (NETA, volume 13)
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Generally, a discrete time RNN can be described by the difference system model
where x ∈ R n , F : R n → R n is a mapping which can be bounded or unbounded. By suitably selecting the mapping F in (8.1), various classes of discrete RNNs can be obtained.
$$ x(k + 1) = F(x(k)) $$
KeywordsEquilibrium Point Convergence Analysis Recurrent Neural Network Cellular Neural Network Complete Convergence
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.
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© Springer Science+Business Media Dordrecht 2004