An experimental unification of reservoir computing methods

@article{Verstraeten2007AnEU,
  title={An experimental unification of reservoir computing methods},
  author={David Verstraeten and Benjamin Schrauwen and Michiel D'Haene and Dirk Stroobandt},
  journal={Neural networks : the official journal of the International Neural Network Society},
  year={2007},
  volume={20 3},
  pages={391-403}
}
Three different uses of a recurrent neural network (RNN) as a reservoir that is not trained but instead read out by a simple external classification layer have been described in the literature: Liquid State Machines (LSMs), Echo State Networks (ESNs) and the Backpropagation Decorrelation (BPDC) learning rule. Individual descriptions of these techniques exist, but a overview is still lacking. Here, we present a series of experimental results that compares all three implementations, and draw… CONTINUE READING
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