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Estimate time-series covariance functions.
Syntax
R = covf(data,M) R = covf(data,M,maxsize)
Description
data
is an iddata
object and M
is the maximum delay -1 for which the covariance function is estimated.
Let z
contain the output and input channels:
z = [data.OutputData, data.InputData]
R
is returned as an nz2 -by- M matrix with entries
where is the
j
-th column of z
and missing values in the sum are replaced by zero.
The optional argument maxsize
controls the memory size as explained under Algorithm Properties
.
The easiest way to describe and unpack the result is to use
reshape(R(:,k+1),nz,nz) = E z(t)*z'(t+k)
Here '
is complex conjugate transpose, which also explains how complex data are handled. The expectation symbol E
corresponds to the sample means.
Algorithm
When nz
is at most two, and when permitted by maxsize
, a fast Fourier transform technique is applied. Otherwise, straightforward summing is used.
See Also
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