JavaRNN use full connected RNNs. Such a RNN contains X nodes and X2 connections.
Each of this connection is weighted. The choosen transfer function is at this time
a simple sigmoid.
We actually use RNN as predictor : we check the RNN capability to predict a signal
at T+1. We also use it as long-run predcitor, coupling its predicted output to
its input we let im predict a signal at T+n
We have experienced limitations modelling periodic signals due to the natural resonant frequency
of the RNN. To solve this problem we had delay buffers in each connection in form of
a FIFO queue. the length of the queue is also set during the training.