Volterra-Wiener Characterization
Volterra-Wiener characterization of non-linear dynamic systems subjected to Gaussian white noise input signal.
function [h0,h1,h2]=Volterra_Wiener_Id(x,y,MaxLag1,MaxLag2)
Input
x: input signal of size (N*1)
y: output signal of size (N*1)
MaxLag1: Max number of lags for the first kernel
MaxLag2: Max number of lags for the second kernel
output
h0: zero order kernel
h1: first oder kernel of size(MaxLag1+1,1)
h2: second order kernel of size(MaxLag2+1,MaxLag2+1)
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Identified model can be verified by forecasting ouput from the input with the identified kernels using the following function:
function y=Volterra_Wiener_Forecast(x,h0,h1,h2)
Input
x: input signal of size (N*1)
h0: zero order kernel
h1: first oder kernel of size(MaxLag1+1,1)
h2: second order kernel of size(MaxLag2+1,MaxLag2+1)
output
y: output signal of size (N*1)
Cite As
Ayad Al-Rumaithi (2024). Volterra-Wiener Characterization (https://www.mathworks.com/matlabcentral/fileexchange/71799-volterra-wiener-characterization), MATLAB Central File Exchange. Retrieved .
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