Automatica (Journal of IFAC)
Generalized Kernel Regression Estimate for the Identification of Hammerstein Systems
International Journal of Applied Mathematics and Computer Science
| Hi-index | 35.69 |
Nonlinear systems constituted by a zero-memory nonlinearity cascaded with linear filters can be identified by input-output cross correlation using a Gaussian input signal. The method is extended to complex systems through a pair of complex invariance theorems. The stated properties allow identifying the linear parts of systems characterized by magnitude/phase nonlinearities with the joint use of second- and third-order input-output moments. The method can be employed for a wide class of communication bandpass circuits when signals are represented by complex envelopes