User`s guide

Identifying Hammerstein-Wiener Models
information about model orders, see “Definition of the Hammerstein-Wiener
Model” on page 4-15.
InputNonlinearity specifies the input static nonlinearity estimator object
as
'pwlinear', 'deadzone', 'saturation' , 'sigmoidnet ', 'wavenet',
'customnet', 'unitgain',or'poly1d'. Similarly, OutputNonlinearity
specifies the output s tatic nonlinearity estim ator object.
The property-value pairs specify any
idnlhw model properties that configure
the estimation algorithm. You can enter all model pro perty -v alue pairs
and top-level alg orithm properties as a comma-separated list in
nlhw.For
example, you can control the iterative search for a best fit using the following
properties:
m = nlhw(data,'nb',nb,...
'nf',nf,...
'nk',nk,...
InputNonlinearity,...
OutputNonlinearity,...
'MaxIter',N,...
'Tolerance',tol,...
'LimitError',lim,
'Display','on')
Note You do not need to construct the model object using idnlhw before
estimation.
nlhw both constructs and estim ates the model.
For nu inputs and ny outputs, na, nb,andnk are ny-by-nu matrices whose
i-jth entry specifies the order and delay of the transfer function from the
jth input to the ith output.
4-21