Optimum Experimental Design for Locally Recurrent Networks

A fundamental problem underlying the training of neural networks is the selection of proper input data to provide good representation of the modelled system behaviour [77, 7]. This problem comprises the determination of a limited number of observational units obtained from the experimental environment in such a way as to obtain the best quality of the system responses.