Robustness quantification of recurrent neural network using unscented transform

Artificial recurrent neural network has been proved to be a valuable tool in modeling nonlinear dynamical systems. Robustness study of recurrent neural network is critical to its successful implementation. The goal of robustness study is to reduce the sensitivity of modeling capability to parametric uncertainties or make the network fault tolerant. In this… (More)