Improving the approximation ability of Volterra series identified with a cross-correlation method

This paper proposes an improvement in cross-correlation methods derived from the Lee-Schetzen method, in order to obtain a lower mean square error in the output for a wider range of the input variances. In particular, each Wiener kernel is identified with a different input variance and new formulas for conversion from Wiener to Volterra representation are presented.