IDENTIFICATION OF A CLASS OF NONLINEAR-SYSTEMS UNDER STATIONARY NON-GAUSSIAN EXCITATION

This paper provides new solutions to the nonlinear system identificati on problem when the input to the system is a stationary non-Gaussian p rocess. We propose the use of a model called the Hammerstein series, w hich leads to significant reductions in both the computational require ments and the mathematical tractability of the nonlinear system identi fication problem. We show that unlike the Volterra series, one can obt ain closed-form expressions for the Hammerstein series kernels and the quadratic coherence function in the non-Gaussian case. Estimation of the kernels and quadratic coherence function is discussed. A compariso n with a nonlinear system identification approach that uses the Volter ra series is provided. An automotive engineering application illustrat es the usefulness of the proposed method.