Prediction of trajectories using a simple one hidden layer Elman Network using only numpy.
One file contains the trajectory and the idea is to have another variable that is just one time step further than the original trajectory, get predicted.
We have two inputs, two outputs, which represent the x and y co-ordinates, and five hidden (and thus context) layers.
The data file is uploaded to the elman_rnn repo