Estimate frequency response with fixed frequency resolution using spectral analysis

`G = spa(data)`

G = spa(data,winSize,freq)

G = spa(data,winSize,freq,MaxSize)

`G = spa(data)`

estimates frequency response
(with uncertainty) and noise spectrum from time- or frequency-domain
data. `data`

is an `iddata`

or `idfrd`

object
and can be complex valued. `G`

is as an `idfrd`

object.
For time-series `data`

, `G`

is the
estimated spectrum and standard deviation.

Information about the estimation results and options used is
stored in the model's `Report`

property. `Report`

has
the following fields:

`Status`

— Summary of the model status, which indicates whether the model was created by construction or obtained by estimation.`Method`

— Estimation command used.`WindowSize`

— Size of the Hann window.`DataUsed`

— Attributes of the data used for estimation. Structure with the following fields:`Name`

— Name of the data set.`Type`

— Data type.`Length`

— Number of data samples.`Ts`

— Sample time.`InterSample`

— Input intersample behavior.`InputOffset`

— Offset removed from time-domain input data during estimation.`OutputOffset`

— Offset removed from time-domain output data during estimation.

`G = spa(data,winSize,freq)`

estimates frequency
response at frequencies `freq`

. `freq`

is
a row vector of values in rad/sec. `winSize`

is a
scalar integer that sets the size of the Hann window.

`G = spa(data,winSize,freq,MaxSize)`

can
improve computational performance using `MaxSize`

to
split the input-output data such that each segment contains fewer
than `MaxSize`

elements. `MaxSize`

is
a positive integer.

Ljung, L. *System Identification: Theory for the User*,
Second Ed., Prentice Hall PTR, 1999.

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