Multiple-variance cross-correlation method for Volterra series identification

Multiple-variance Volterra series identification

The multiple-variance identification method exploits input signals with different variances for nonlinear system identification with Volterra series.
It overcomes the problem of the locality of Volterra series identified with traditional identification methods, like those based on cross-correlation, that well approximate the system only for inputs that have approximately the same power of the identification signal.