New files added to the Volterra-Wiener tool:

ident_volt.m      :Identification of Wiener system with algorithm proposed in 
[1] Simone Orcioni, Massimiliano Pirani, and Claudio Turchetti. Advances in
Lee-Schetzen method for Volterra filter identification. Multidimensional
Systems and Signal Processing, 16(3):265-284, 2005.

ident_volt_20.m  :Identification of Wiener system with the mukltiple-variance
algorithm proposed in
[2] Simone Orcioni. Improving the approximation ability of Volterra series 
identified with a cross-correlation method. Nonlinear Dynamics, 2014.

Wiener2Volterra_20.m : Formulas for Wiener to Volterra conversion for
mukltiple-variance algorithm.

In the directory examples you can find the code used in [2] to obtain all
published results.

The multiple variance algorithm has been updated to use the computational 
complexity reduction method presented in 
[3] Orcioni, S., Terenzi, A., Cecchi, S., Piazza, F., & Carini, A. (2018). 
Identification of Volterra Models of Tube Audio Devices using 
Multiple-Variance Method. Journal of the Audio Engineering Society, 
66(10), 823–838. https://doi.org/10.17743/jaes.2018.0046