RECURSIVE CONSTRUCTION OF PERIODIC STEADY-STATE FOR NEURAL NETWORKS

We present a strategy in order to build neural networks with long stea dy-state periodic behavior. This strategy allows us to obtain 2(n) non equivalent neural networks of size n, when the equivalence relation is the usual one in dynamical systems. As a particular case, we build a neural network with n neurons which realizes a cycle of period 2(n).