Existence, learning, and replication of periodic motions in recurrent neural networks
A. Ruiz, D.H. Owens, Stuart Townley · IEEE Transactions on Neural Networks · 1998
A class of recurrent neural networks is shown to possess a stable limit cycle. A gradient type algorithm is used to modify the parameters of the network so that it learns and replicates autonomously a time varying periodic signal. The results are applied to controlling the repetitive motion of a two-link robot manipulator.