Nr is the number of regressors, ex: if you have x={u(k-1),u(k-2),y(k-1),y(k-2)}, then Nr=4.
wavelet hammerstein wiener model
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Hi all, the below expression was found from http://www.mathworks.com/help/toolbox/ident/ref/wavenet.html
F(x)=(x-r)PL + a s_1f(bs_1((x-r)Q-cs_1))+... as_nsf(bs_ns((x-r)Q-cs_ns))+...aw_1g(bw_1((x-r)Q-cw_1))+...+aw_nwg(bw_nw((x-r)Q-cw_nw))+d
f is a scaling function.
g is the wavelet function.
where by
f(x)=exp(-0.5xx’)
g(x)=(Nr-xx’)exp(-0.5xx’)
where Nr is the length of x (number of regressors).
I need some help from all to understand the definition of Nr. Can anyone define the Nr to help me understand better?
And
Let say x=[ 6 7 8 9 10 11];
If g(6), what is the value of Nr?
If g(7), what is the value of Nr?
If g(8), what is the value of Nr?
Thanks.
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