Interval Identification of Nonlinear Systems using Neural Networks

In this paper, the enveloping method is used to evaluate an interval extension of system model when the output error is unknown but bounded. The envelope is determined using neural networks such that it contains the true system model. To this extend the pattern learning scheme is used to update neural networks for sigmoidal transfer functions is both hidden and output layers.